diff --git a/6.bulk_Morphology_Elastic_Network/2.test_model/notebooks/1.test_regression_multi_output.ipynb b/6.bulk_Morphology_Elastic_Network/2.test_model/notebooks/1.test_regression_multi_output.ipynb index 8f8b83b82..385a1d0d9 100644 --- a/6.bulk_Morphology_Elastic_Network/2.test_model/notebooks/1.test_regression_multi_output.ipynb +++ b/6.bulk_Morphology_Elastic_Network/2.test_model/notebooks/1.test_regression_multi_output.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -21,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -35,12 +35,16 @@ "cell_type = args.cell_type\n", "shuffle = ast.literal_eval(args.shuffle)\n", "cytokine = args.cytokine\n", - "print(cell_type, shuffle, cytokine)" + "print(cell_type, shuffle, cytokine)\n", + "\n", + "# cell_type = \"PBMC\"\n", + "# shuffle = False\n", + "# cytokine = \"XCL1 (Lymphotactin) [NSU]\"" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -51,7 +55,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -64,7 +68,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -73,7 +77,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -93,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -108,7 +112,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -118,7 +122,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -129,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -140,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -170,35 +174,43 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(71, 1199) (71, 187) (83, 1199) (83, 187)\n" + ] + } + ], "source": [ "print(train_data_x.shape, train_data_y.shape, test_data_x.shape, test_data_y.shape)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "# set model path from parameters\n", "if (aggregation == True) and (nomic == True):\n", - " model_path = pathlib.Path(f\"models/regression/{cell_type}/aggregated_with_nomic/\")\n", + " model_path = pathlib.Path(f\"models/regression/{cell_type}_aggregated_with_nomic/\")\n", "elif (aggregation == True) and (nomic == False):\n", - " model_path = pathlib.Path(f\"models/regression/{cell_type}/aggregated/\")\n", + " model_path = pathlib.Path(f\"models/regression/{cell_type}_aggregated/\")\n", "elif (aggregation == False) and (nomic == True):\n", - " model_path = pathlib.Path(f\"models/regression/{cell_type}/sc_with_nomic/\")\n", + " model_path = pathlib.Path(f\"models/regression/{cell_type}_sc_with_nomic/\")\n", "elif (aggregation == False) and (nomic == False):\n", - " model_path = pathlib.Path(f\"models/regression/{cell_type}/sc/\")\n", + " model_path = pathlib.Path(f\"models/regression/{cell_type}_sc/\")\n", "else:\n", " print(\"Error\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -220,7 +232,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -230,7 +242,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -257,79 +269,318 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ - "data_x = test_data_x\n", - "data_y = test_data_y\n", - "metadata = metadata_test\n", - "data_split = \"test\"\n", - "if shuffle == \"shuffled_baseline\":\n", - " model = joblib.load(\n", - " f\"../../1.train_models/{model_path}/{cytokine}_shuffled_baseline__all_nomic.joblib\"\n", - " )\n", - "elif shuffle == \"final\":\n", - " model = joblib.load(\n", - " f\"../../1.train_models/{model_path}/{cytokine}_final__all_nomic.joblib\"\n", - " )\n", - "else:\n", - " print(\"Error\")\n", + "list_of_dfs = []\n", + "for data_split in data_dict.keys():\n", + " data_x = data_dict[data_split][\"data_x\"]\n", + " data_y = data_dict[data_split][\"data_y\"]\n", + " col_names = data_dict[data_split][\"col_names\"]\n", + " metadata = data_dict[data_split][\"metadata\"]\n", "\n", - "# get the cytokine column of choice\n", - "y_selected = data_y[cytokine]\n", + " if shuffle == \"shuffled_baseline\":\n", + " model = joblib.load(\n", + " f\"../../1.train_models/{model_path}/{cytokine}_shuffled_baseline__all_nomic.joblib\"\n", + " )\n", + " elif shuffle == \"final\":\n", + " model = joblib.load(\n", + " f\"../../1.train_models/{model_path}/{cytokine}_final__all_nomic.joblib\"\n", + " )\n", + " else:\n", + " print(\"Error\")\n", "\n", - "if shuffle == \"shuffled_baseline\":\n", - " for column in data_x:\n", - " np.random.shuffle(data_x[column].values)\n", + " # get the cytokine column of choice\n", + " y_selected = data_y[cytokine]\n", "\n", - "# get predictions\n", - "predictions = model.predict(data_x)\n", + " if shuffle == \"shuffled_baseline\":\n", + " for column in data_x:\n", + " np.random.shuffle(data_x[column].values)\n", "\n", - "explained_variance = explained_variance_score(y_selected, predictions)\n", - "output_metric_scores[\"explained_variance\"] = explained_variance\n", - "neg_mean_absolute_error = -mean_squared_error(y_selected, predictions)\n", - "output_metric_scores[\"neg_mean_absolute_error\"] = neg_mean_absolute_error\n", - "neg_mean_squared_error = -mean_squared_error(y_selected, predictions)\n", - "output_metric_scores[\"neg_mean_squared_error\"] = neg_mean_squared_error\n", - "r2 = r2_score(y_selected, predictions)\n", - "output_metric_scores[\"treatment\"] = metadata[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "]\n", - "output_metric_scores[\"well\"] = metadata[\"Metadata_Well\"].values\n", - "df = pd.DataFrame.from_dict(output_metric_scores)\n", - "df[\"r2\"] = r2\n", - "df[\"cytokine\"] = cytokine\n", - "df[\"data_split\"] = data_split\n", - "df[\"shuffle\"] = shuffle\n", - "df[\"predicted_value\"] = predictions\n", - "df[\"actual_value\"] = y_selected\n", - "df[\"log10_neg_mean_absolute_error\"] = -np.log10(-df[\"neg_mean_absolute_error\"])\n", - "df[\"log10_neg_mean_squared_error\"] = -np.log10(-df[\"neg_mean_squared_error\"])\n", - "df[\"log10_explained_variance\"] = -np.log10(df[\"explained_variance\"])\n", + " # get predictions\n", + " predictions = model.predict(data_x)\n", "\n", - "# replace \"[NSU]\" with \"\"\"\n", - "df[\"cytokine\"] = df[\"cytokine\"].replace(\"[ \\[\\]NSU]\", \"\", regex=True)\n", - "df[\"cytokine\"] = df[\"cytokine\"].replace(\" \", \"_\", regex=True)\n", + " explained_variance = explained_variance_score(y_selected, predictions)\n", + " output_metric_scores[\"explained_variance\"] = explained_variance\n", + " neg_mean_absolute_error = -mean_squared_error(y_selected, predictions)\n", + " output_metric_scores[\"neg_mean_absolute_error\"] = neg_mean_absolute_error\n", + " neg_mean_squared_error = -mean_squared_error(y_selected, predictions)\n", + " output_metric_scores[\"neg_mean_squared_error\"] = neg_mean_squared_error\n", + " r2 = r2_score(y_selected, predictions)\n", + " output_metric_scores[\"treatment\"] = metadata[\n", + " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", + " ]\n", + " output_metric_scores[\"well\"] = metadata[\"Metadata_Well\"].values\n", + " df = pd.DataFrame.from_dict(output_metric_scores)\n", + " df[\"r2\"] = r2\n", + " df[\"cytokine\"] = cytokine\n", + " df[\"data_split\"] = data_split\n", + " df[\"shuffle\"] = shuffle\n", + " df[\"predicted_value\"] = predictions\n", + " df[\"actual_value\"] = y_selected\n", + " df[\"log10_neg_mean_absolute_error\"] = -np.log10(-df[\"neg_mean_absolute_error\"])\n", + " df[\"log10_neg_mean_squared_error\"] = -np.log10(-df[\"neg_mean_squared_error\"])\n", + " df[\"log10_explained_variance\"] = -np.log10(df[\"explained_variance\"])\n", "\n", - "# concat the dataframes\n", - "results_df = pd.concat([results_df, df], axis=0)" + " # replace \"[NSU]\" with \"\"\"\n", + " df[\"cytokine\"] = df[\"cytokine\"].replace(\"[ \\[\\]NSU]\", \"\", regex=True)\n", + " df[\"cytokine\"] = df[\"cytokine\"].replace(\" \", \"_\", regex=True)\n", + " list_of_dfs.append(df)\n", + " # concat the dataframes\n", + "results_df = pd.concat(list_of_dfs, axis=0)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
explained_varianceneg_mean_absolute_errorneg_mean_squared_errortreatmentwellr2cytokinedata_splitshufflepredicted_valueactual_valuelog10_neg_mean_absolute_errorlog10_neg_mean_squared_errorlog10_explained_variance
50.727112-0.007897-0.007897DMSO_0.100_%_DMSO_0.025_%B070.727112XCL1(Lymphotactin)train_datafinal0.2745720.1670782.102562.102560.138399
60.727112-0.007897-0.007897LPS_0.010_ug_per_ml_DMSO_0.025_%B080.727112XCL1(Lymphotactin)train_datafinal0.3922710.5052522.102562.102560.138399
80.727112-0.007897-0.007897LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...B100.727112XCL1(Lymphotactin)train_datafinal0.3795610.5111842.102562.102560.138399
90.727112-0.007897-0.007897LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...B110.727112XCL1(Lymphotactin)train_datafinal0.3854010.2791162.102562.102560.138399
100.727112-0.007897-0.007897MediaB120.727112XCL1(Lymphotactin)train_datafinal0.3130910.2971582.102562.102560.138399
\n", + "
" + ], + "text/plain": [ + " explained_variance neg_mean_absolute_error neg_mean_squared_error \\\n", + "5 0.727112 -0.007897 -0.007897 \n", + "6 0.727112 -0.007897 -0.007897 \n", + "8 0.727112 -0.007897 -0.007897 \n", + "9 0.727112 -0.007897 -0.007897 \n", + "10 0.727112 -0.007897 -0.007897 \n", + "\n", + " treatment well r2 \\\n", + "5 DMSO_0.100_%_DMSO_0.025_% B07 0.727112 \n", + "6 LPS_0.010_ug_per_ml_DMSO_0.025_% B08 0.727112 \n", + "8 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... B10 0.727112 \n", + "9 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... B11 0.727112 \n", + "10 Media B12 0.727112 \n", + "\n", + " cytokine data_split shuffle predicted_value actual_value \\\n", + "5 XCL1(Lymphotactin) train_data final 0.274572 0.167078 \n", + "6 XCL1(Lymphotactin) train_data final 0.392271 0.505252 \n", + "8 XCL1(Lymphotactin) train_data final 0.379561 0.511184 \n", + "9 XCL1(Lymphotactin) train_data final 0.385401 0.279116 \n", + "10 XCL1(Lymphotactin) train_data final 0.313091 0.297158 \n", + "\n", + " log10_neg_mean_absolute_error log10_neg_mean_squared_error \\\n", + "5 2.10256 2.10256 \n", + "6 2.10256 2.10256 \n", + "8 2.10256 2.10256 \n", + "9 2.10256 2.10256 \n", + "10 2.10256 2.10256 \n", + "\n", + " log10_explained_variance \n", + "5 0.138399 \n", + "6 0.138399 \n", + "8 0.138399 \n", + "9 0.138399 \n", + "10 0.138399 " + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "results_df.head()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
cytokinedata_splitshufflepredicted_valueactual_valuer2
0XCL1(Lymphotactin)test_datafinal0.0204730.030055[0.57914177985185]
1XCL1(Lymphotactin)train_datafinal0.0180820.029351[0.727111789960502]
\n", + "
" + ], + "text/plain": [ + " cytokine data_split shuffle predicted_value actual_value \\\n", + "0 XCL1(Lymphotactin) test_data final 0.020473 0.030055 \n", + "1 XCL1(Lymphotactin) train_data final 0.018082 0.029351 \n", + "\n", + " r2 \n", + "0 [0.57914177985185] \n", + "1 [0.727111789960502] " + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "var_df = results_df.drop(\n", " columns=[\n", @@ -358,21 +609,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# set model path from parameters\n", "if (aggregation == True) and (nomic == True):\n", " results_path = pathlib.Path(\n", - " f\"../results/regression/{cell_type}/aggregated_with_nomic/\"\n", + " f\"../results/regression/{cell_type}_aggregated_with_nomic/\"\n", " )\n", "elif (aggregation == True) and (nomic == False):\n", - " results_path = pathlib.Path(f\"../results/regression/{cell_type}/aggregated/\")\n", + " results_path = pathlib.Path(f\"../results/regression/{cell_type}_aggregated/\")\n", "elif (aggregation == False) and (nomic == True):\n", - " results_path = pathlib.Path(f\"../results/regression/{cell_type}/sc_with_nomic/\")\n", + " results_path = pathlib.Path(f\"../results/regression/{cell_type}_sc_with_nomic/\")\n", "elif (aggregation == False) and (nomic == False):\n", - " results_path = pathlib.Path(f\"../results/regression/{cell_type}/sc/\")\n", + " results_path = pathlib.Path(f\"../results/regression/{cell_type}_sc/\")\n", "else:\n", " print(\"Error\")\n", "pathlib.Path(results_path).mkdir(parents=True, exist_ok=True)" @@ -380,7 +631,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -403,7 +654,7 @@ "formats": "ipynb,../scripts//py:percent" }, "kernelspec": { - "display_name": "Interstellar", + "display_name": "Interstellar_python", "language": "python", "name": "python3" }, @@ -417,7 +668,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.10.15" } }, "nbformat": 4, diff --git a/6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/PBMC_aggregated_with_nomic/.gitkeep b/6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/PBMC_aggregated_with_nomic/.gitkeep deleted file mode 100644 index e69de29bb..000000000 diff --git a/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/1.test_regression_multi_output.py b/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/1.test_regression_multi_output.py index 062dbdb10..8aecffec7 100644 --- a/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/1.test_regression_multi_output.py +++ b/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/1.test_regression_multi_output.py @@ -1,7 +1,7 @@ #!/usr/bin/env python # coding: utf-8 -# In[ ]: +# In[1]: import argparse @@ -16,7 +16,7 @@ from sklearn.metrics import explained_variance_score, mean_squared_error, r2_score from sklearn.utils import parallel_backend -# In[ ]: +# In[2]: argparser = argparse.ArgumentParser() @@ -31,8 +31,12 @@ cytokine = args.cytokine print(cell_type, shuffle, cytokine) +# cell_type = "PBMC" +# shuffle = False +# cytokine = "XCL1 (Lymphotactin) [NSU]" -# In[ ]: + +# In[3]: # Parameters @@ -40,7 +44,7 @@ nomic = True -# In[ ]: +# In[4]: # set shuffle value @@ -50,13 +54,13 @@ shuffle = "final" -# In[ ]: +# In[5]: MODEL_TYPE = "regression" -# In[ ]: +# In[6]: # load training data from indexes and features dataframe @@ -73,7 +77,7 @@ data_split_indexes = pd.read_csv(data_split_path, sep="\t") -# In[ ]: +# In[7]: # rename column that contain the treatment dose to be a metadata column @@ -85,14 +89,14 @@ ) -# In[ ]: +# In[8]: # remove duplicate columns data_df = data_df.loc[:, ~data_df.columns.duplicated()] -# In[ ]: +# In[9]: # select tht indexes for the training and test set @@ -100,7 +104,7 @@ test_indexes = data_split_indexes.loc[data_split_indexes["label"] == "test"] -# In[ ]: +# In[10]: # subset data_df by indexes in data_split_indexes @@ -108,7 +112,7 @@ testing_data = data_df.loc[test_indexes["labeled_data_index"]] -# In[ ]: +# In[11]: # define metadata columns @@ -135,29 +139,29 @@ test_data_x = test_data_x.drop(test_data_y_cols, axis=1) -# In[ ]: +# In[12]: print(train_data_x.shape, train_data_y.shape, test_data_x.shape, test_data_y.shape) -# In[ ]: +# In[13]: # set model path from parameters if (aggregation == True) and (nomic == True): - model_path = pathlib.Path(f"models/regression/{cell_type}/aggregated_with_nomic/") + model_path = pathlib.Path(f"models/regression/{cell_type}_aggregated_with_nomic/") elif (aggregation == True) and (nomic == False): - model_path = pathlib.Path(f"models/regression/{cell_type}/aggregated/") + model_path = pathlib.Path(f"models/regression/{cell_type}_aggregated/") elif (aggregation == False) and (nomic == True): - model_path = pathlib.Path(f"models/regression/{cell_type}/sc_with_nomic/") + model_path = pathlib.Path(f"models/regression/{cell_type}_sc_with_nomic/") elif (aggregation == False) and (nomic == False): - model_path = pathlib.Path(f"models/regression/{cell_type}/sc/") + model_path = pathlib.Path(f"models/regression/{cell_type}_sc/") else: print("Error") -# In[ ]: +# In[14]: data_dict = { @@ -176,14 +180,14 @@ } -# In[ ]: +# In[15]: # list of metrics to use output_metric_scores = {} -# In[ ]: +# In[16]: # blank df for concatenated results @@ -207,71 +211,74 @@ ) -# In[ ]: +# In[17]: + + +list_of_dfs = [] +for data_split in data_dict.keys(): + data_x = data_dict[data_split]["data_x"] + data_y = data_dict[data_split]["data_y"] + col_names = data_dict[data_split]["col_names"] + metadata = data_dict[data_split]["metadata"] + + if shuffle == "shuffled_baseline": + model = joblib.load( + f"../../1.train_models/{model_path}/{cytokine}_shuffled_baseline__all_nomic.joblib" + ) + elif shuffle == "final": + model = joblib.load( + f"../../1.train_models/{model_path}/{cytokine}_final__all_nomic.joblib" + ) + else: + print("Error") + + # get the cytokine column of choice + y_selected = data_y[cytokine] + + if shuffle == "shuffled_baseline": + for column in data_x: + np.random.shuffle(data_x[column].values) + + # get predictions + predictions = model.predict(data_x) + + explained_variance = explained_variance_score(y_selected, predictions) + output_metric_scores["explained_variance"] = explained_variance + neg_mean_absolute_error = -mean_squared_error(y_selected, predictions) + output_metric_scores["neg_mean_absolute_error"] = neg_mean_absolute_error + neg_mean_squared_error = -mean_squared_error(y_selected, predictions) + output_metric_scores["neg_mean_squared_error"] = neg_mean_squared_error + r2 = r2_score(y_selected, predictions) + output_metric_scores["treatment"] = metadata[ + "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" + ] + output_metric_scores["well"] = metadata["Metadata_Well"].values + df = pd.DataFrame.from_dict(output_metric_scores) + df["r2"] = r2 + df["cytokine"] = cytokine + df["data_split"] = data_split + df["shuffle"] = shuffle + df["predicted_value"] = predictions + df["actual_value"] = y_selected + df["log10_neg_mean_absolute_error"] = -np.log10(-df["neg_mean_absolute_error"]) + df["log10_neg_mean_squared_error"] = -np.log10(-df["neg_mean_squared_error"]) + df["log10_explained_variance"] = -np.log10(df["explained_variance"]) + # replace "[NSU]" with """ + df["cytokine"] = df["cytokine"].replace("[ \[\]NSU]", "", regex=True) + df["cytokine"] = df["cytokine"].replace(" ", "_", regex=True) + list_of_dfs.append(df) + # concat the dataframes +results_df = pd.concat(list_of_dfs, axis=0) -data_x = test_data_x -data_y = test_data_y -metadata = metadata_test -data_split = "test" -if shuffle == "shuffled_baseline": - model = joblib.load( - f"../../1.train_models/{model_path}/{cytokine}_shuffled_baseline__all_nomic.joblib" - ) -elif shuffle == "final": - model = joblib.load( - f"../../1.train_models/{model_path}/{cytokine}_final__all_nomic.joblib" - ) -else: - print("Error") -# get the cytokine column of choice -y_selected = data_y[cytokine] - -if shuffle == "shuffled_baseline": - for column in data_x: - np.random.shuffle(data_x[column].values) - -# get predictions -predictions = model.predict(data_x) - -explained_variance = explained_variance_score(y_selected, predictions) -output_metric_scores["explained_variance"] = explained_variance -neg_mean_absolute_error = -mean_squared_error(y_selected, predictions) -output_metric_scores["neg_mean_absolute_error"] = neg_mean_absolute_error -neg_mean_squared_error = -mean_squared_error(y_selected, predictions) -output_metric_scores["neg_mean_squared_error"] = neg_mean_squared_error -r2 = r2_score(y_selected, predictions) -output_metric_scores["treatment"] = metadata[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -] -output_metric_scores["well"] = metadata["Metadata_Well"].values -df = pd.DataFrame.from_dict(output_metric_scores) -df["r2"] = r2 -df["cytokine"] = cytokine -df["data_split"] = data_split -df["shuffle"] = shuffle -df["predicted_value"] = predictions -df["actual_value"] = y_selected -df["log10_neg_mean_absolute_error"] = -np.log10(-df["neg_mean_absolute_error"]) -df["log10_neg_mean_squared_error"] = -np.log10(-df["neg_mean_squared_error"]) -df["log10_explained_variance"] = -np.log10(df["explained_variance"]) - -# replace "[NSU]" with """ -df["cytokine"] = df["cytokine"].replace("[ \[\]NSU]", "", regex=True) -df["cytokine"] = df["cytokine"].replace(" ", "_", regex=True) - -# concat the dataframes -results_df = pd.concat([results_df, df], axis=0) - - -# In[ ]: +# In[18]: results_df.head() -# In[ ]: +# In[19]: var_df = results_df.drop( @@ -299,26 +306,26 @@ var_df.head() -# In[ ]: +# In[20]: # set model path from parameters if (aggregation == True) and (nomic == True): results_path = pathlib.Path( - f"../results/regression/{cell_type}/aggregated_with_nomic/" + f"../results/regression/{cell_type}_aggregated_with_nomic/" ) elif (aggregation == True) and (nomic == False): - results_path = pathlib.Path(f"../results/regression/{cell_type}/aggregated/") + results_path = pathlib.Path(f"../results/regression/{cell_type}_aggregated/") elif (aggregation == False) and (nomic == True): - results_path = pathlib.Path(f"../results/regression/{cell_type}/sc_with_nomic/") + results_path = pathlib.Path(f"../results/regression/{cell_type}_sc_with_nomic/") elif (aggregation == False) and (nomic == False): - results_path = pathlib.Path(f"../results/regression/{cell_type}/sc/") + results_path = pathlib.Path(f"../results/regression/{cell_type}_sc/") else: print("Error") pathlib.Path(results_path).mkdir(parents=True, exist_ok=True) -# In[ ]: +# In[21]: # check if the model training metrics file exists diff --git a/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/2.combine_regression_tests.py b/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/2.combine_regression_tests.py index 6bd932c47..c7fcf88e8 100644 --- a/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/2.combine_regression_tests.py +++ b/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/2.combine_regression_tests.py @@ -4,7 +4,6 @@ # In[1]: -import argparse import pathlib import pandas as pd @@ -12,27 +11,29 @@ # In[2]: -argparser = argparse.ArgumentParser() -argparser.add_argument("--cell_type", type=str, default="cell_type") +# argparser = argparse.ArgumentParser() +# argparser.add_argument("--cell_type", type=str, default="cell_type") -args = argparser.parse_args() +# args = argparser.parse_args() -cell_type = args.cell_type +# cell_type = args.cell_type +cell_type = "PBMC" -# In[ ]: + +# In[3]: results_dir_path = pathlib.Path( - f"../results/regression/{cell_type}/aggregated_with_nomic/" + f"../results/regression/{cell_type}_aggregated_with_nomic/" ).resolve(strict=True) model_stats_final_output_path = pathlib.Path( - f"../results/regression/{cell_type}/aggregated_with_nomic/model_stats.csv" + f"../results/regression/{cell_type}_aggregated_with_nomic/model_stats.csv" ) variance_r2_stats_final_output_path = pathlib.Path( - f"../results/regression/{cell_type}/aggregated_with_nomic/variance_r2_stats.csv" + f"../results/regression/{cell_type}_aggregated_with_nomic/variance_r2_stats.csv" ) # get a list of all the files that contain "model_stats" in the name @@ -54,7 +55,22 @@ variance_r2_stats_df.to_csv(variance_r2_stats_final_output_path, index=False) -# In[ ]: +# In[4]: print("Completed!") + + +# In[5]: + + +model_stats_df.head() + + +# In[6]: + + +model_stats_df["data_split"].unique() + + +# In[ ]: diff --git a/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/3.visualize_regression_multi_output.r b/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/3.visualize_regression_multi_output.r deleted file mode 100644 index 80666dad2..000000000 --- a/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/3.visualize_regression_multi_output.r +++ /dev/null @@ -1,412 +0,0 @@ -suppressWarnings(suppressPackageStartupMessages(library(ggplot2))) -suppressWarnings(suppressPackageStartupMessages(library(platetools))) -suppressWarnings(suppressPackageStartupMessages(library(gridExtra))) -suppressWarnings(suppressPackageStartupMessages(library(cowplot))) -suppressWarnings(suppressPackageStartupMessages(library(viridis))) -suppressWarnings(suppressPackageStartupMessages(library(argparse))) - -cell_type <- "PBMC" - - -df_stats_path <- file.path( - paste0("../results/regression/",cell_type,"/aggregated_with_nomic/model_stats.csv" - ) -) -df_variance_path <- file.path( - paste0("../results/regression/",cell_type,"/aggregated_with_nomic/variance_r2_stats.csv" - ) -) -# import csv file -df <- read.csv(df_stats_path) -df_var <- read.csv(df_variance_path) - -# set up figure path -enet_cp_fig_path <- paste0("../figures/regression/",cell_type,"/aggregated_with_nomic/") - - -# if path does not exist, create it -if (!file.exists(dirname(enet_cp_fig_path))) { - print(dirname(enet_cp_fig_path)) - dir.create(dirname(enet_cp_fig_path), recursive = TRUE) -} - -print(unique(df$shuffle)) -print(length(unique(df$cytokine))) - -options(repr.plot.width=6, repr.plot.height=5) -# set output path -global_prediction_trend_path <- file.path(paste0(enet_cp_fig_path,"global_prediction_trend.png")) -# if path does not exist, create it -if (!file.exists(dirname(global_prediction_trend_path))) { - print(dirname(global_prediction_trend_path)) - dir.create(dirname(global_prediction_trend_path), recursive = TRUE) -} -# plot the data -global_prediction_trend_scatter <- ( - ggplot(df, aes(x=actual_value, y=predicted_value, col=shuffle)) - + geom_point(alpha=0.5, size=0.5) - # add geom smooth with each line being a different color - + labs(x="Actual", y="Predicted") - + theme_bw() - + labs(title="Global Prediction Trends of Cytokine Concentrations") - # add y=x line - + geom_abline(intercept = 0, slope = 1, linetype="dashed", color="black") - + facet_wrap(data_split~shuffle, ncol=2) -) - -# save the plot -ggsave(global_prediction_trend_path, global_prediction_trend_scatter, width=5, height=5, dpi=500) -global_prediction_trend_scatter - -global_prediction_trend_line <- ( - ggplot(df, aes(x=actual_value, y=predicted_value, col=shuffle)) - # add geom smooth with each line being a different color - + geom_smooth(method="lm", se=TRUE, alpha=0.5, size=0.5, aes(col=shuffle)) - # make colors different for each line - + scale_fill_gradientn(colours = viridis(10)) - + labs(x="Actual", y="Predicted") - + theme_bw() - + labs(title="Global Prediction Trends of Cytokine Concentrations") - # add y=x line - + geom_abline(intercept = 0, slope = 1, linetype="dashed", color="black") - + facet_wrap(data_split~shuffle, ncol=2) - + ylim(0, 1) - + xlim(0, 1) -) -ggsave(global_prediction_trend_path, global_prediction_trend_line, width=5, height=5, dpi=500) -global_prediction_trend_line - -df$shuffle_plus_data_split <- paste0(df$shuffle, "_", df$data_split) -# replace 'final_test_data' with 'Final + Test' and 'final_train_data' with 'Final + Train' -df$shuffle_plus_data_split <- gsub("final_test_data", "Final + Test", df$shuffle_plus_data_split) -df$shuffle_plus_data_split <- gsub("final_train_data", "Final + Train", df$shuffle_plus_data_split) -df$shuffle_plus_data_split <- gsub("shuffled_baseline_test_data", "Shuffled + Test", df$shuffle_plus_data_split) -df$shuffle_plus_data_split <- gsub("shuffled_baseline_train_data", "Shuffled + Train", df$shuffle_plus_data_split) - -enet_cp_fig <- file.path(paste0(enet_cp_fig_path,"Predicted_vs_Actual_all_cytokines.pdf")) -pdf(file=enet_cp_fig) -# set plot size -options(repr.plot.width=6, repr.plot.height=4) -# facet by secrete -for (i in 1:length(unique(df$cytokine))){ - sub_df <- df[df$cytokine == (unique(df$cytokine)[i]),] -# plot -p <- ( - ggplot(sub_df, aes(x=actual_value, y=predicted_value, col=shuffle_plus_data_split)) - + geom_point() - + theme_bw() - + geom_smooth(method=lm, se=TRUE, formula = y ~ x, alpha=0.5, size=0.5) - + labs(x="Actual", y="Predicted") - - + ggtitle(unique(df$cytokine)[i]) - + ylim(0, 1) - + xlim(0, 1) - + theme( - axis.text.x = element_text(size = 12), - axis.text.y = element_text(size = 12), - axis.title.x = element_text(size = 16), - axis.title.y = element_text(size = 16), - # center the title - plot.title = element_text(hjust = 0.5) - ) - + labs(color="Model", hjust=0.5) - - # change facet label size - + theme(strip.text.x = element_text(size = 12)) - + theme(strip.text.y = element_text(size = 12)) - # change legend text size - + theme(legend.text=element_text(size=12)) - # change legend title size - + theme(legend.title=element_text(size=14)) - # change legend title - # make kegend key background white - + guides(color = guide_legend(override.aes = list(fill = NA)), - linetype = guide_legend(override.aes = list(fill = NA))) - + theme(legend.key = element_rect(fill = "white")) - ) - plot(p) -} -dev.off() - - -# remove '[]' from the string in the column -df_var$r2 <- gsub("\\[|\\]", "", df_var$r2) -# set the column as numeric -df_var$r2 <- as.numeric(df_var$r2) -head(df_var) - -# set plot size -options(repr.plot.width=5, repr.plot.height=5) -# set output path -global_variance_r2_path <- file.path(paste0(enet_cp_fig_path,"global_variance_r2.png")) -# if path does not exist, create it -if (!file.exists(dirname(global_prediction_trend_path))) { - print(dirname(global_prediction_trend_path)) - dir.create(dirname(global_prediction_trend_path), recursive = TRUE) -} -# plot df_var df -variance_r2_plot <- ( - ggplot(df_var, aes(x=r2, y=actual_value,col=shuffle, shape = data_split)) - + geom_point() - # + geom_smooth(method=lm, se=TRUE) - + labs(x="r2", y="variance") - + theme_bw() -) -ggsave(global_variance_r2_path, variance_r2_plot, width=5, height=5, dpi=500) -variance_r2_plot - -local_variance_r2_path <- file.path(paste0(enet_cp_fig_path,"local_variance_r2.png")) -local_variance_r2_legend_path <- file.path(paste0(enet_cp_fig_path,"local_variance_r2_legend.png")) -# if path does not exist, create it -if (!file.exists(dirname(global_prediction_trend_path))) { - print(dirname(global_prediction_trend_path)) - dir.create(dirname(global_prediction_trend_path), recursive = TRUE) -} -# same plot but only in the positive quadrant -variance_r2_plot <- ( - ggplot(df_var, aes(x=r2, y=actual_value, col=shuffle, shape = data_split)) - + geom_point(size=3) - + labs(x="R2 score", y="Explained Variance") - + theme_bw() - + xlim(0, max(df_var$r2)) - + ylim(0, max(df_var$actual_value)) - # change the x and y axis text size - + theme( - axis.text.x = element_text(size=13), - axis.text.y = element_text(size=13), - legend.text=element_text(size=16), - axis.title=element_text(size=16), - legend.title=element_text(size=16) - ) - # make legend points bigger - + guides( - colour = guide_legend(override.aes = list(size=3)), - shape = guide_legend(override.aes = list(size=3)) - ) -) -legend <- get_legend(variance_r2_plot) -variance_r2_plot <- variance_r2_plot + theme(legend.position = "none") -ggsave(local_variance_r2_path, variance_r2_plot, width=5, height=5, dpi=500) -ggsave(local_variance_r2_legend_path, legend, width=5, height=5, dpi=500) -variance_r2_plot -plot(legend) - -# remove all cytokines that have r2 < 0 for both test and train set -neg_r2 <- df_var[df_var$r2 < 0,] -remove_cytokine_list <- neg_r2[neg_r2$shuffle == "final",]$cytokine -# remove cytokines from df -df_var <- df_var[!(df_var$cytokine %in% remove_cytokine_list),] -# create a new column tha combine the shuffle columnm and the data_split column -df_var$shuffle_data_split <- paste0(df_var$shuffle, "_", df_var$data_split) - - -# set size of the plot -options(repr.plot.width=26, repr.plot.height=10) -# get only the final models -# df_var_final <- df_var[df_var$shuffle == "final",] -# set the order of the cytokines by the r2 score for the test set -# df_var_final$cytokine <- factor(df_var_pos$cytokine, levels = df_var_pos[order(df_var_pos$r2, decreasing = TRUE),]$cytokine) -# plot the df_var_pos df on a bar plot -variance_r2_bar_plot <- ( - ggplot(df_var, aes(x = reorder(cytokine, r2, decreasing=T), y=r2, fill=shuffle_data_split)) - + geom_bar(stat="identity", position=position_dodge()) - + labs(x="Shuffle", y="R2 score") - + theme_bw() - + theme(legend.text=element_text(size=16)) - # make x ticks labels larger and rotate them 90 degrees - + theme(axis.text.x = element_text(size=16, angle=90, hjust=1)) - -) -# get the legend -legend <- get_legend(variance_r2_bar_plot) -# remove the legend -variance_r2_bar_plot <- variance_r2_bar_plot + theme(legend.position="none") - -ggsave(file.path(paste0(enet_cp_fig_path,"variance_r2_bar_plot.png")), variance_r2_bar_plot, width=26, height=10, dpi=500) -ggsave(file.path(paste0(enet_cp_fig_path,"variance_r2_bar_plot_legend.png")), legend, width=5, height=5, dpi=500) -variance_r2_bar_plot -options(repr.plot.width=5, repr.plot.height=5) -plot(legend) - -# calculate the se of each metric for each shuffle, data_split, and cytokine in R -agg_df <- aggregate(log10_neg_mean_absolute_error ~ shuffle + data_split + cytokine + treatment, df, function(x) c(mean = mean(x), sd = sd(x))) -# split the log10_neg_mean_absolute_error column into two columns -agg_df <- cbind(agg_df, agg_df$log10_neg_mean_absolute_error) -# remove the log10_neg_mean_absolute_error column by name -agg_df <- agg_df[, !names(agg_df) %in% c('log10_neg_mean_absolute_error')] -# rename the columns -colnames(agg_df) <- c("shuffle", "data_split", "cytokine", "treatment","mean_log10_neg_mean_absolute_error", "sd_log10_neg_mean_absolute_error") - - -# set output path -prediction_metric <- file.path(paste0(enet_cp_fig_path,"prediction_metric.png")) -# if path does not exist, create it -if (!file.exists(dirname(global_prediction_trend_path))) { - print(dirname(global_prediction_trend_path)) - dir.create(dirname(global_prediction_trend_path), recursive = TRUE) -} -# set plot size -options(repr.plot.width=30, repr.plot.height=12) - - - -# plot a bar plot of the mean log10_neg_mean_absolute_error for each data split, cytokine, and shuffle with error bars -bar_plot <- ( - ggplot(agg_df, aes(x=cytokine, y=mean_log10_neg_mean_absolute_error, fill=cytokine)) - + geom_bar(stat="identity", position=position_dodge()) - + geom_errorbar(aes(ymin=mean_log10_neg_mean_absolute_error-sd_log10_neg_mean_absolute_error, ymax=mean_log10_neg_mean_absolute_error+sd_log10_neg_mean_absolute_error), width=.2, position=position_dodge(.9)) - + labs(x="Data Split", y="log10_neg_mean_absolute_error") - + theme_bw() - + theme(axis.text.x = element_text(angle = 90, hjust = 1)) - + facet_wrap(data_split ~ shuffle, ncol=1) - #add viridis color scale - + scale_fill_viridis(discrete = TRUE, option = "inferno", direction = -1) - # order the x axis by the mean of the log10_neg_mean_absolute_error - # + scale_x_discrete(limits = temp_agg_df$cytokine[order(temp_agg_df$mean_log10_neg_mean_absolute_error)]) -) -# detach the legend -# get the legend from the plot -bar_plot <- bar_plot + theme(legend.position="none") -ggsave(prediction_metric, bar_plot, width=30, height=12, dpi=500) -print(bar_plot) - - -# per cytokine graph -file_path <- file.path(paste0(enet_cp_fig_path)) -# if path does not exist, create it -if (!file.exists(dirname(file_path))) { - print(dirname(file_path)) - dir.create(dirname(file_path), recursive = TRUE) -} -pdf(file=file.path(paste0(file_path,"individual_cytokine_prediction_metric.pdf"))) -for ( i in 1:length(unique(agg_df$cytokine))){ - # print(unique(agg_df$cytokine)[i]) - # set output path - # set plot size - options(repr.plot.width=12, repr.plot.height=12) - # plot a bar plot of the mean log10_neg_mean_absolute_error for each data split, cytokine, and shuffle with error bars - tmp_df <- agg_df[agg_df$cytokine == unique(agg_df$cytokine)[i],] - # get the mean and sd of the log10_neg_mean_absolute_error for each data split, cytokine, and shuffle - tmp_df <- aggregate(mean_log10_neg_mean_absolute_error ~ shuffle + data_split, tmp_df, function(x) c(mean = mean(x), sd = sd(x))) - # split the log10_neg_mean_absolute_error column into two columns - tmp_df <- cbind(tmp_df, tmp_df$mean_log10_neg_mean_absolute_error) - # drop the log10_neg_mean_absolute_error column by name - tmp_df <- tmp_df[, !names(tmp_df) %in% c('mean_log10_neg_mean_absolute_error')] - # split the mean_log10_neg_mean_absolute_error column into two columns - - tmp_plot <- ( - ggplot(tmp_df, aes(x=data_split, y=mean, fill=shuffle)) - + geom_bar(stat="identity", position=position_dodge()) - + geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd), width=.2, position=position_dodge(.9)) - + labs(x="Data Split", y="log10_neg_mean_absolute_error") - + ggtitle(unique(agg_df$cytokine)[i]) - + theme_bw() - + theme( - axis.text.x = element_text(hjust = 1, size=16), - axis.text.y = element_text(size=16), - axis.title.x = element_text(size=20), - axis.title.y = element_text(size=20), - plot.title = element_text(size=20) - ) - + ylab("-log10(MSE)") - ) - plot(tmp_plot) -} -dev.off() - -# set lists to iterate over -list_of_cytokines <- unique(df$cytokine) -list_of_data_frames <- list('final', 'shuffled_baseline') - -pdf(file=file.path(paste0(enet_cp_fig_path,"prediction_per_well_platemap_all_cytokines.pdf")) - ) -# set plot size -options(repr.plot.width=8, repr.plot.height=8) -for (df_type in (list_of_data_frames)){ - for (cytokine in list_of_cytokines){ - # if statement to determine which dataframe to use - # filter for shuffled data or non-shuffled data - if (df_type == 'final'){ - shuffle_type_df <- df[df$shuffle == "final",] - title <- paste0("Predictive Performance of ", cytokine, " per Well (Final model)") - } else if (df_type == 'shuffled_baseline'){ - shuffle_type_df <- df[df$shuffle == "shuffled_baseline",] - title <- paste0("Predictive Performance of ", cytokine, " per Well (Shuffled_baseline model)") - } - # from the shuffled data, filter for the cytokine of interest - cytokine_df <- shuffle_type_df[shuffle_type_df$cytokine == cytokine,] - # plot the data on a plate map - platemap_plot <- ( - raw_map( - data = cytokine_df$log10_neg_mean_absolute_error, - well = cytokine_df$well, - plate = 384) - + ggtitle(title) - + theme_dark() - + ggplot2::geom_point(aes(shape = cytokine_df$data_split)) - ) - plot(platemap_plot) - } -} -dev.off() - -treatment_well_platemap <- file.path(paste0(enet_cp_fig_path,"treatment_platemap.png")) -# plot size set -options(repr.plot.width=12, repr.plot.height=8) -platemap_plot <- ( - raw_map( - data = df$treatment, - well = df$well, - plate = 384) - + ggtitle("Selected Treatment Platemap") - + theme_dark() -) -ggsave(treatment_well_platemap, platemap_plot, width=12, height=8, dpi=500) -platemap_plot - -# generate a platemap plot for the meta data -# read in the platemap data -platemap_df_path <- "../../../data/Interstellar_plate2_platemap.csv" -platemap_df <- read.csv(platemap_df_path) -# if cell_type is blank, set it to "blank" -platemap_df$cell_type[platemap_df$cell_type == ""] <- "blank" -# if treatment is blank, set it to "blank" -platemap_df$inducer1[platemap_df$inducer1 == ""] <- "blank" - -# plot size -options(repr.plot.width=8, repr.plot.height=8) -# platemap of experimental contitions (cell type and inducer) -cell_type_well_platemap <- file.path(paste0(enet_cp_fig_path,"cell_type_well_platemap.png")) -# if path does not exist, create it -if (!file.exists(dirname(global_prediction_trend_path))) { - print(dirname(global_prediction_trend_path)) - dir.create(dirname(global_prediction_trend_path), recursive = TRUE) -} -platemap_plot <- ( - raw_map( - data = platemap_df$cell_type, - well = platemap_df$well_id, - plate = 384) - + theme_dark() -) -ggsave(cell_type_well_platemap, platemap_plot, width=5, height=5, dpi=500) -platemap_plot - - -inducer_well_platemap <- file.path(paste0(enet_cp_fig_path,"inducer_well_platemap.png")) -# if path does not exist, create it -if (!file.exists(dirname(global_prediction_trend_path))) { - print(dirname(global_prediction_trend_path)) - dir.create(dirname(global_prediction_trend_path), recursive = TRUE) -} -platemap_plot <- ( - raw_map( - data = platemap_df$inducer1, - well = platemap_df$well_id, - plate = 384) - + theme_dark() - + ggplot2::geom_point(aes(shape = platemap_df$cell_type)) -) -ggsave(inducer_well_platemap, platemap_plot, width=8, height=8, dpi=500) -platemap_plot - diff --git a/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/test_model_call_local.sh b/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/test_model_call_local.sh index 2fa2f88d2..d80e3ad25 100644 --- a/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/test_model_call_local.sh +++ b/6.bulk_Morphology_Elastic_Network/2.test_model/scripts/test_model_call_local.sh @@ -12,7 +12,7 @@ readarray -t cytokine_array < $filename shuffles=( "True" "False" ) -cell_types=( PBMC SHSY5Y ) +cell_types=( PBMC ) # calculate total iterations total_iterations=$((${#cytokine_array[@]} * ${#shuffles[@]} * ${#cell_types[@]})) diff --git a/9.mAP/notebooks/0.generate_map_scores_morphology.ipynb b/9.mAP/notebooks/0.generate_map_scores_morphology.ipynb index 387be620c..731604c6e 100644 --- a/9.mAP/notebooks/0.generate_map_scores_morphology.ipynb +++ b/9.mAP/notebooks/0.generate_map_scores_morphology.ipynb @@ -6,36 +6,22 @@ "metadata": {}, "outputs": [], "source": [ - "import itertools\n", - "import logging\n", + "import argparse\n", "import pathlib\n", - "import sys\n", - "from typing import Optional\n", + "import random\n", "\n", "import numpy as np\n", "import pandas as pd\n", "import toml\n", - "from copairs.map import run_pipeline\n", - "from pycytominer import feature_select\n", + "from copairs import map\n", + "from copairs.matching import assign_reference_index\n", "\n", - "# imports src\n", - "sys.path.append(\"../\")\n", - "from src import utils\n", - "\n", - "# setting up logger\n", - "logging.basicConfig(\n", - " filename=\"map_analysis_testing.log\",\n", - " level=logging.DEBUG,\n", - " format=\"%(levelname)s:%(asctime)s:%(name)s:%(message)s\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Helper functions\n", - "Set of helper functions to help out throughout the notebook" + "# check if in a jupyter notebook\n", + "try:\n", + " cfg = get_ipython().config\n", + " in_notebook = True\n", + "except NameError:\n", + " in_notebook = False" ] }, { @@ -44,95 +30,14 @@ "metadata": {}, "outputs": [], "source": [ - "## Helper function\n", - "\n", - "\n", - "def shuffle_meta_labels(\n", - " dataset: pd.DataFrame, target_col: str, seed: Optional[int] = 0\n", - ") -> pd.DataFrame:\n", - " \"\"\"shuffles labels or values within a single selected column\n", - "\n", - " Parameters\n", - " ----------\n", - " dataset : pd.DataFrame\n", - " dataframe containing the dataset\n", - "\n", - " target_col : str\n", - " Column to select in order to conduct the shuffling\n", - "\n", - " seed : int\n", - " setting random seed\n", - "\n", - " Returns\n", - " -------\n", - " pd.DataFrame\n", - " shuffled dataset\n", - "\n", - " Raises\n", - " ------\n", - " TypeError\n", - " raised if incorrect types are provided\n", - " \"\"\"\n", - " # setting seed\n", - " np.random.seed(seed)\n", - "\n", - " # type checking\n", - " if not isinstance(target_col, str):\n", - " raise TypeError(\"'target_col' must be a string type\")\n", - " if not isinstance(dataset, pd.DataFrame):\n", - " raise TypeError(\"'dataset' must be a pandas dataframe\")\n", - "\n", - " # selecting column, shuffle values within column, add to dataframe\n", - " dataset[target_col] = np.random.permutation(dataset[target_col].values)\n", - " return dataset\n", - "\n", - "\n", - "def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.array:\n", - " \"\"\"suffles all values within feature space\n", - "\n", - " Parameters\n", - " ----------\n", - " feature_vals : np.array\n", - " shuffled\n", - "\n", - " seed : Optional[int]\n", - " setting random seed\n", + "if not in_notebook:\n", + " parser = argparse.ArgumentParser(description=\"Match pairs of samples\")\n", + " parser.add_argument(\"--shuffle\", action=\"store_true\", help=\"Shuffle the data\")\n", "\n", - " Returns\n", - " -------\n", - " np.array\n", - " Returns shuffled values within the feature space\n", - "\n", - " Raisespairs(sameby=pos_s\n", - " TypeError\n", - " Raised if a numpy array is not provided\n", - " \"\"\"\n", - " # setting seed\n", - " np.random.seed(seed)\n", - "\n", - " # shuffle given array\n", - " if not isinstance(feature_vals, np.ndarray):\n", - " raise TypeError(\"'feature_vals' must be a numpy array\")\n", - " if feature_vals.ndim != 2:\n", - " raise TypeError(\"'feature_vals' must be a 2x2 matrix\")\n", - "\n", - " # creating a copy for feature vales to prevent overwriting of global variables\n", - " feature_vals = np.copy(feature_vals)\n", - "\n", - " # shuffling feature space\n", - " n_cols = feature_vals.shape[1]\n", - " for col_idx in range(0, n_cols):\n", - " # selecting column, shuffle, and update:\n", - " # feature_vals[:, col_idx] = np.random.permutation(feature_vals[:, col_idx])\n", - " np.random.shuffle(feature_vals[:, col_idx])\n", - " return feature_vals" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setting up Paths and loading data" + " args = parser.parse_args()\n", + " shuffle = args.shuffle\n", + "else:\n", + " shuffle = True" ] }, { @@ -149,19 +54,311 @@ "ground_truth = toml.load(ground_truth)\n", "apoptosis_ground_truth = ground_truth[\"Apoptosis\"][\"apoptosis_groups_list\"]\n", "pyroptosis_ground_truth = ground_truth[\"Pyroptosis\"][\"pyroptosis_groups_list\"]\n", - "control_ground_truth = ground_truth[\"Healthy\"][\"healthy_groups_list\"]" + "control_ground_truth = ground_truth[\"Healthy\"][\"healthy_groups_list\"]\n", + "\n", + "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/morphology/\")\n", + "map_out_dir.mkdir(exist_ok=True, parents=True)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Metadata_WellMetadata_TreatmentCytoplasm_AreaShape_CompactnessCytoplasm_AreaShape_FormFactorCytoplasm_AreaShape_MajorAxisLengthCytoplasm_AreaShape_MinorAxisLengthCytoplasm_AreaShape_OrientationCytoplasm_AreaShape_Zernike_0_0Cytoplasm_AreaShape_Zernike_1_1Cytoplasm_AreaShape_Zernike_2_0...Nuclei_Texture_InverseDifferenceMoment_CorrER_3_03_256Nuclei_Texture_InverseDifferenceMoment_CorrMito_3_02_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_00_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_01_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_02_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_03_256Nuclei_Texture_SumEntropy_CorrPM_3_01_256Nuclei_Texture_SumVariance_CorrPM_3_03_256Nuclei_Texture_Variance_CorrER_3_02_256Nuclei_Texture_Variance_CorrMito_3_01_256
0B02LPS_0.010_ug_per_ml_DMSO_0.025_%0.100173-0.0597340.2185670.1119380.007420-0.100946-0.030356-0.070701...0.021386-0.095924-0.182695-0.185317-0.183084-0.1894340.2172710.023909-0.015452-0.004886
1B03LPS_0.010_ug_per_ml_DMSO_0.025_%0.137279-0.0976460.2056440.108021-0.002159-0.141895-0.059932-0.091195...0.0346470.079415-0.105950-0.112622-0.108821-0.1141370.1411560.022128-0.017276-0.006272
2B04LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...0.071345-0.0535660.0554040.0133730.004443-0.111708-0.084402-0.043409...-0.087337-0.671670-0.068129-0.062520-0.063204-0.0665420.074449-0.0200610.0222860.039616
3B05LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...0.110685-0.0843460.1079540.0719230.004150-0.121376-0.075382-0.052805...-0.096255-1.263923-0.102173-0.099375-0.101330-0.1006250.114060-0.0072270.0094580.059863
4B06DMSO_0.100_%_DMSO_0.025_%-0.0217710.018442-0.048689-0.070490-0.005284-0.008255-0.012815-0.017174...0.0826420.2923180.0298050.0229690.0264960.024827-0.028355-0.007840-0.037983-0.014871
\n", + "

5 rows \u00d7 1201 columns

\n", + "
" + ], + "text/plain": [ + " Metadata_Well Metadata_Treatment \\\n", + "0 B02 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", + "1 B03 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", + "2 B04 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", + "3 B05 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", + "4 B06 DMSO_0.100_%_DMSO_0.025_% \n", + "\n", + " Cytoplasm_AreaShape_Compactness Cytoplasm_AreaShape_FormFactor \\\n", + "0 0.100173 -0.059734 \n", + "1 0.137279 -0.097646 \n", + "2 0.071345 -0.053566 \n", + "3 0.110685 -0.084346 \n", + "4 -0.021771 0.018442 \n", + "\n", + " Cytoplasm_AreaShape_MajorAxisLength Cytoplasm_AreaShape_MinorAxisLength \\\n", + "0 0.218567 0.111938 \n", + "1 0.205644 0.108021 \n", + "2 0.055404 0.013373 \n", + "3 0.107954 0.071923 \n", + "4 -0.048689 -0.070490 \n", + "\n", + " Cytoplasm_AreaShape_Orientation Cytoplasm_AreaShape_Zernike_0_0 \\\n", + "0 0.007420 -0.100946 \n", + "1 -0.002159 -0.141895 \n", + "2 0.004443 -0.111708 \n", + "3 0.004150 -0.121376 \n", + "4 -0.005284 -0.008255 \n", + "\n", + " Cytoplasm_AreaShape_Zernike_1_1 Cytoplasm_AreaShape_Zernike_2_0 ... \\\n", + "0 -0.030356 -0.070701 ... \n", + "1 -0.059932 -0.091195 ... \n", + "2 -0.084402 -0.043409 ... \n", + "3 -0.075382 -0.052805 ... \n", + "4 -0.012815 -0.017174 ... \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrER_3_03_256 \\\n", + "0 0.021386 \n", + "1 0.034647 \n", + "2 -0.087337 \n", + "3 -0.096255 \n", + "4 0.082642 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrMito_3_02_256 \\\n", + "0 -0.095924 \n", + "1 0.079415 \n", + "2 -0.671670 \n", + "3 -1.263923 \n", + "4 0.292318 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_00_256 \\\n", + "0 -0.182695 \n", + "1 -0.105950 \n", + "2 -0.068129 \n", + "3 -0.102173 \n", + "4 0.029805 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_01_256 \\\n", + "0 -0.185317 \n", + "1 -0.112622 \n", + "2 -0.062520 \n", + "3 -0.099375 \n", + "4 0.022969 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_02_256 \\\n", + "0 -0.183084 \n", + "1 -0.108821 \n", + "2 -0.063204 \n", + "3 -0.101330 \n", + "4 0.026496 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_03_256 \\\n", + "0 -0.189434 \n", + "1 -0.114137 \n", + "2 -0.066542 \n", + "3 -0.100625 \n", + "4 0.024827 \n", + "\n", + " Nuclei_Texture_SumEntropy_CorrPM_3_01_256 \\\n", + "0 0.217271 \n", + "1 0.141156 \n", + "2 0.074449 \n", + "3 0.114060 \n", + "4 -0.028355 \n", + "\n", + " Nuclei_Texture_SumVariance_CorrPM_3_03_256 \\\n", + "0 0.023909 \n", + "1 0.022128 \n", + "2 -0.020061 \n", + "3 -0.007227 \n", + "4 -0.007840 \n", + "\n", + " Nuclei_Texture_Variance_CorrER_3_02_256 \\\n", + "0 -0.015452 \n", + "1 -0.017276 \n", + "2 0.022286 \n", + "3 0.009458 \n", + "4 -0.037983 \n", + "\n", + " Nuclei_Texture_Variance_CorrMito_3_01_256 \n", + "0 -0.004886 \n", + "1 -0.006272 \n", + "2 0.039616 \n", + "3 0.059863 \n", + "4 -0.014871 \n", + "\n", + "[5 rows x 1201 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "single_cell_data = pathlib.Path(\n", - " f\"../../data/PBMC_preprocessed_sc_norm_aggregated.parquet\"\n", + "agg_data = pathlib.Path(\n", + " \"../../data/PBMC_preprocessed_sc_norm_aggregated.parquet\"\n", ").resolve(strict=True)\n", - "df = pd.read_parquet(single_cell_data)" + "df = pd.read_parquet(agg_data)\n", + "# rename oneb_Metadata_Treatment_Dose_Inhibitor_Dose to Metadata_Treatment\n", + "df = df.rename(\n", + " columns={\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\": \"Metadata_Treatment\"}\n", + ")\n", + "df.head()" ] }, { @@ -169,51 +366,18 @@ "execution_count": 5, "metadata": {}, "outputs": [], - "source": [ - "# out paths\n", - "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/morphology/\")\n", - "map_out_dir.mkdir(exist_ok=True, parents=True)\n", - "\n", - "# regular data output\n", - "# saving to csv\n", - "regular_feat_map_path = pathlib.Path(map_out_dir / \"mAP_scores_regular_class.csv\")\n", - "\n", - "# shuffled data output\n", - "shuffled_feat_map_path = pathlib.Path(map_out_dir / \"mAP_scores_shuffled_class.csv\")\n", - "\n", - "# shuffled feature space output\n", - "shuffled_feat_space_map_path = pathlib.Path(\n", - " map_out_dir / \"mAP_scores_shuffled_feature_space_class.csv\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Clean up data" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], "source": [ "# add apoptosis, pyroptosis and healthy columns to dataframe\n", "df[\"Apoptosis\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in apoptosis_ground_truth,\n", + " lambda row: row[\"Metadata_Treatment\"] in apoptosis_ground_truth,\n", " axis=1,\n", ")\n", "df[\"Pyroptosis\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in pyroptosis_ground_truth,\n", + " lambda row: row[\"Metadata_Treatment\"] in pyroptosis_ground_truth,\n", " axis=1,\n", ")\n", "df[\"Control\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in control_ground_truth,\n", + " lambda row: row[\"Metadata_Treatment\"] in control_ground_truth,\n", " axis=1,\n", ")\n", "\n", @@ -226,148 +390,339 @@ " else \"Control\",\n", " axis=1,\n", ")\n", + "metadata_labels = df.pop(\"Metadata_labels\")\n", + "df.insert(1, \"Metadata_labels\", metadata_labels)\n", "# # drop apoptosis, pyroptosis, and healthy columns\n", - "df.drop(columns=[\"Apoptosis\", \"Pyroptosis\", \"Control\"], inplace=True)\n", - "df.drop(columns=[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"], inplace=True)" + "df.drop(columns=[\"Apoptosis\", \"Pyroptosis\", \"Control\"], inplace=True)" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ - "# output directories\n", - "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/\")\n", - "map_out_dir.mkdir(parents=True, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP Pipeline Parameters" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The null size needs to be determined for the mAP pipeline. This is the size of the null class that is used to determine the mAP score." + "if shuffle:\n", + " random.seed(0)\n", + " # permutate the data\n", + " for col in df.columns:\n", + " df[col] = np.random.permutation(df[col])" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Metadata_WellMetadata_labelsMetadata_TreatmentCytoplasm_AreaShape_CompactnessCytoplasm_AreaShape_FormFactorCytoplasm_AreaShape_MajorAxisLengthCytoplasm_AreaShape_MinorAxisLengthCytoplasm_AreaShape_OrientationCytoplasm_AreaShape_Zernike_0_0Cytoplasm_AreaShape_Zernike_1_1...Nuclei_Texture_InverseDifferenceMoment_CorrMito_3_02_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_00_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_01_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_02_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_03_256Nuclei_Texture_SumEntropy_CorrPM_3_01_256Nuclei_Texture_SumVariance_CorrPM_3_03_256Nuclei_Texture_Variance_CorrER_3_02_256Nuclei_Texture_Variance_CorrMito_3_01_256Metadata_reference_index
0B03ControlFlagellin_0.100_ug_per_ml_DMSO_0.025_%0.212101-0.0862660.1998210.023845-0.019501-0.136982-0.043793...-0.1123430.1304650.099233-0.031162-0.085304-0.005050-0.0142380.017012-0.011485-1
1O12PyroptosisLPS_0.100_ug_per_ml_DMSO_0.025_%0.1582130.018494-0.0868380.020259-0.004711-0.0261490.066402...-0.0729850.011064-0.068718-0.1352110.068626-0.017263-0.040739-0.018409-0.007831-1
2L06ControlFlagellin_1.000_ug_per_ml_Disulfiram_1.000_uM-0.0751210.0954940.0601430.125031-0.017194-0.145544-0.044858...-0.3609000.1346890.0865780.095933-0.286537-0.0782580.013157-0.0122770.023380-1
3K03PyroptosisThapsigargin_1.000_uM_DMSO_0.025_%0.127851-0.039661-0.0371660.0514030.010892-0.169862-0.065433...0.229581-0.1222040.138037-0.045380-0.0128200.082831-0.049986-0.0035500.021821-1
4G02PyroptosisTopotecan_5.000_nM_DMSO_0.025_%0.076874-0.0094820.2152230.084962-0.0079590.012145-0.073524...0.8726690.002117-0.280193-0.1566170.0264330.0668460.035393-0.001726-0.004956-1
\n", + "

5 rows \u00d7 1203 columns

\n", + "
" + ], "text/plain": [ - "65" + " Metadata_Well Metadata_labels \\\n", + "0 B03 Control \n", + "1 O12 Pyroptosis \n", + "2 L06 Control \n", + "3 K03 Pyroptosis \n", + "4 G02 Pyroptosis \n", + "\n", + " Metadata_Treatment \\\n", + "0 Flagellin_0.100_ug_per_ml_DMSO_0.025_% \n", + "1 LPS_0.100_ug_per_ml_DMSO_0.025_% \n", + "2 Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM \n", + "3 Thapsigargin_1.000_uM_DMSO_0.025_% \n", + "4 Topotecan_5.000_nM_DMSO_0.025_% \n", + "\n", + " Cytoplasm_AreaShape_Compactness Cytoplasm_AreaShape_FormFactor \\\n", + "0 0.212101 -0.086266 \n", + "1 0.158213 0.018494 \n", + "2 -0.075121 0.095494 \n", + "3 0.127851 -0.039661 \n", + "4 0.076874 -0.009482 \n", + "\n", + " Cytoplasm_AreaShape_MajorAxisLength Cytoplasm_AreaShape_MinorAxisLength \\\n", + "0 0.199821 0.023845 \n", + "1 -0.086838 0.020259 \n", + "2 0.060143 0.125031 \n", + "3 -0.037166 0.051403 \n", + "4 0.215223 0.084962 \n", + "\n", + " Cytoplasm_AreaShape_Orientation Cytoplasm_AreaShape_Zernike_0_0 \\\n", + "0 -0.019501 -0.136982 \n", + "1 -0.004711 -0.026149 \n", + "2 -0.017194 -0.145544 \n", + "3 0.010892 -0.169862 \n", + "4 -0.007959 0.012145 \n", + "\n", + " Cytoplasm_AreaShape_Zernike_1_1 ... \\\n", + "0 -0.043793 ... \n", + "1 0.066402 ... \n", + "2 -0.044858 ... \n", + "3 -0.065433 ... \n", + "4 -0.073524 ... \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrMito_3_02_256 \\\n", + "0 -0.112343 \n", + "1 -0.072985 \n", + "2 -0.360900 \n", + "3 0.229581 \n", + "4 0.872669 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_00_256 \\\n", + "0 0.130465 \n", + "1 0.011064 \n", + "2 0.134689 \n", + "3 -0.122204 \n", + "4 0.002117 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_01_256 \\\n", + "0 0.099233 \n", + "1 -0.068718 \n", + "2 0.086578 \n", + "3 0.138037 \n", + "4 -0.280193 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_02_256 \\\n", + "0 -0.031162 \n", + "1 -0.135211 \n", + "2 0.095933 \n", + "3 -0.045380 \n", + "4 -0.156617 \n", + "\n", + " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_03_256 \\\n", + "0 -0.085304 \n", + "1 0.068626 \n", + "2 -0.286537 \n", + "3 -0.012820 \n", + "4 0.026433 \n", + "\n", + " Nuclei_Texture_SumEntropy_CorrPM_3_01_256 \\\n", + "0 -0.005050 \n", + "1 -0.017263 \n", + "2 -0.078258 \n", + "3 0.082831 \n", + "4 0.066846 \n", + "\n", + " Nuclei_Texture_SumVariance_CorrPM_3_03_256 \\\n", + "0 -0.014238 \n", + "1 -0.040739 \n", + "2 0.013157 \n", + "3 -0.049986 \n", + "4 0.035393 \n", + "\n", + " Nuclei_Texture_Variance_CorrER_3_02_256 \\\n", + "0 0.017012 \n", + "1 -0.018409 \n", + "2 -0.012277 \n", + "3 -0.003550 \n", + "4 -0.001726 \n", + "\n", + " Nuclei_Texture_Variance_CorrMito_3_01_256 Metadata_reference_index \n", + "0 -0.011485 -1 \n", + "1 -0.007831 -1 \n", + "2 0.023380 -1 \n", + "3 0.021821 -1 \n", + "4 -0.004956 -1 \n", + "\n", + "[5 rows x 1203 columns]" ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "tmp = (\n", - " df.groupby([\"Metadata_labels\"])\n", - " .count()\n", - " .reset_index()[[\"Metadata_Well\", \"Metadata_labels\"]]\n", + "reference_col = \"Metadata_reference_index\"\n", + "df_activity = assign_reference_index(\n", + " df,\n", + " \"Metadata_Treatment == 'DMSO_0.100_%_DMSO_0.025_%'\",\n", + " reference_col=reference_col,\n", + " default_value=-1,\n", ")\n", - "# get the Pyroptosis number of Metadata_Well\n", - "Pyroptosis_count = tmp[tmp[\"Metadata_labels\"] == \"Pyroptosis\"][\"Metadata_Well\"].values[\n", - " 0\n", - "]\n", - "Pyroptosis_count" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "pos_sameby = [\n", - " \"Metadata_labels\",\n", - "]\n", - "pos_diffby = [\"Metadata_Well\"]\n", - "\n", - "neg_sameby = []\n", - "neg_diffby = [\"Metadata_labels\"]\n", - "\n", - "null_size = Pyroptosis_count\n", - "batch_size = 1" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP analysis for non-shuffled data" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# generate the permutations of cell death labels via itertools\n", - "pos_samby_permutations = list(itertools.combinations(df[\"Metadata_labels\"].unique(), 2))" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "results_df = pd.DataFrame(\n", - " columns=[\n", - " \"Metadata_Well\",\n", - " \"Metadata_labels\",\n", - " \"average_precision\",\n", - " \"p_value\",\n", - " \"n_pos_pairs\",\n", - " \"n_total_pairs\",\n", - " \"shuffled\",\n", - " \"comparison\",\n", - " ]\n", - ")" + "df_activity.head()" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "33f8d014225443ed95217b379e30f9dc", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/5320 [00:00\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Metadata_WellMetadata_labelsMetadata_TreatmentMetadata_reference_indexn_pos_pairsn_total_pairsaverage_precision
0B03ControlFlagellin_0.100_ug_per_ml_DMSO_0.025_%-12100.625000
1O12PyroptosisLPS_0.100_ug_per_ml_DMSO_0.025_%-12100.173611
2L06ControlFlagellin_1.000_ug_per_ml_Disulfiram_1.000_uM-1190.111111
3K03PyroptosisThapsigargin_1.000_uM_DMSO_0.025_%-13110.303571
4G02PyroptosisTopotecan_5.000_nM_DMSO_0.025_%-12100.225000
\n", + "" + ], "text/plain": [ - " 0%| | 0/2 [00:00\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Metadata_TreatmentMetadata_labelsMetadata_reference_indexmean_average_precisionindicesp_valuecorrected_p_valuebelow_pbelow_corrected_p-log10(p-value)
0DMSO_0.100_%_DMSO_1.000_%Control-10.118056[16, 99]0.8884630.888463FalseFalse0.051361
1DMSO_0.100_%_DMSO_1.000_%Pyroptosis-10.126984[57, 108]0.7773720.838046FalseFalse0.076732
2DMSO_0.100_%_Z-VAD-FMK_100.000_uMControl-10.399242[11, 64, 66, 116]0.4362710.750905FalseFalse0.124415
3DMSO_0.100_%_Z-VAD-FMK_30.000_uMPyroptosis-10.200926[30, 82, 107]0.7999530.838046FalseFalse0.076732
4Disulfiram_0.100_uM_DMSO_0.025_%Control-10.291667[37, 87]0.3333060.637628FalseFalse0.195432
\n", + "" + ], "text/plain": [ - " 0%| | 0/2 [00:00\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_labelsshuffledsampling_errorcomparison
0Apoptosisnon-shuffled0.089180Control_vs_Apoptosis
1Apoptosisnon-shuffled0.090958Pyroptosis_vs_Apoptosis
2Apoptosisshuffled0.017930Control_vs_Apoptosis
3Apoptosisshuffled0.023294Pyroptosis_vs_Apoptosis
4Controlnon-shuffled0.003623Control_vs_Apoptosis
\n", - "" - ], - "text/plain": [ - " Metadata_labels shuffled sampling_error comparison\n", - "0 Apoptosis non-shuffled 0.089180 Control_vs_Apoptosis\n", - "1 Apoptosis non-shuffled 0.090958 Pyroptosis_vs_Apoptosis\n", - "2 Apoptosis shuffled 0.017930 Control_vs_Apoptosis\n", - "3 Apoptosis shuffled 0.023294 Pyroptosis_vs_Apoptosis\n", - "4 Control non-shuffled 0.003623 Control_vs_Apoptosis" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# calculating sampling error\n", - "# grouping dataframe based on phenotype levels, feature and feature types\n", - "df_group = mAPs.groupby(by=[\"Metadata_labels\", \"shuffled\", \"comparison\"])\n", - "df_group\n", - "sampling_error_df = []\n", - "for name, df in df_group:\n", - " pheno, shuffled_type, comparison = name\n", - "\n", - " # caclulating sampling error\n", - " avg_percision = df[\"average_precision\"].values\n", - " sampling_error = np.std(avg_percision) / np.sqrt(len(avg_percision))\n", - "\n", - " sampling_error_df.append([pheno, shuffled_type, sampling_error, comparison])\n", - "cols = [\"Metadata_labels\", \"shuffled\", \"sampling_error\", \"comparison\"]\n", - "sampling_error_df = pd.DataFrame(sampling_error_df, columns=cols)\n", - "\n", - "\n", - "sampling_error_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_labelsmean_average_precisionnlog10pvalueq_valuenlog10qvalueabove_p_thresholdabove_q_thresholdshuffledcomparison
0Apoptosis0.6662993.4128340.0003873.412834TrueTruenon-shuffledControl_vs_Apoptosis
0Apoptosis0.6973763.5001140.0003163.500114TrueTruenon-shuffledPyroptosis_vs_Apoptosis
0Apoptosis0.1636620.7252730.1882460.725273FalseFalseshuffledControl_vs_Apoptosis
0Apoptosis0.1780450.6391220.2295500.639122FalseFalseshuffledPyroptosis_vs_Apoptosis
0Control0.9085110.4331950.3688120.433195FalseFalsenon-shuffledControl_vs_Apoptosis
\n", - "
" - ], - "text/plain": [ - " Metadata_labels mean_average_precision nlog10pvalue q_value \\\n", - "0 Apoptosis 0.666299 3.412834 0.000387 \n", - "0 Apoptosis 0.697376 3.500114 0.000316 \n", - "0 Apoptosis 0.163662 0.725273 0.188246 \n", - "0 Apoptosis 0.178045 0.639122 0.229550 \n", - "0 Control 0.908511 0.433195 0.368812 \n", - "\n", - " nlog10qvalue above_p_threshold above_q_threshold shuffled \\\n", - "0 3.412834 True True non-shuffled \n", - "0 3.500114 True True non-shuffled \n", - "0 0.725273 False False shuffled \n", - "0 0.639122 False False shuffled \n", - "0 0.433195 False False non-shuffled \n", - "\n", - " comparison \n", - "0 Control_vs_Apoptosis \n", - "0 Pyroptosis_vs_Apoptosis \n", - "0 Control_vs_Apoptosis \n", - "0 Pyroptosis_vs_Apoptosis \n", - "0 Control_vs_Apoptosis " - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Generating aggregate scores with a threshold p-value of 0.05\n", - "mAP_dfs = []\n", - "for name, df in tuple(mAPs.groupby(by=[\"Metadata_labels\", \"shuffled\", \"comparison\"])):\n", - " agg_df = aggregate(df, sameby=[\"Metadata_labels\"], threshold=0.05)\n", - " agg_df[\"Metadata_labels\"] = name[0]\n", - " agg_df[\"shuffled\"] = name[1]\n", - " agg_df[\"comparison\"] = name[2]\n", - " mAP_dfs.append(agg_df)\n", - "\n", - "mAP_dfs = pd.concat(mAP_dfs)\n", - "mAP_dfs.to_csv(agg_sc_ap_scores_dir / \"mAP_scores_class.csv\", index=False)\n", - "mAP_dfs.head()" - ] - } - ], - "metadata": { - "interpreter": { - "hash": "2a7bc4b693a428e685bdbc198b90c0fe2d737ece3fda25b7a5d0fc6f41082281" - }, - "kernelspec": { - "display_name": "Python 3.12.0 ('map')", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.2" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.mAP/notebooks/1.generate_map_scores_secretome.ipynb b/9.mAP/notebooks/1.generate_map_scores_secretome.ipynb new file mode 100644 index 000000000..3af6e225d --- /dev/null +++ b/9.mAP/notebooks/1.generate_map_scores_secretome.ipynb @@ -0,0 +1,958 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import argparse\n", + "import pathlib\n", + "import random\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import toml\n", + "from copairs import map\n", + "from copairs.matching import assign_reference_index\n", + "\n", + "# check if in a jupyter notebook\n", + "try:\n", + " cfg = get_ipython().config\n", + " in_notebook = True\n", + "except NameError:\n", + " in_notebook = False" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "if not in_notebook:\n", + " parser = argparse.ArgumentParser(description=\"Match pairs of samples\")\n", + " parser.add_argument(\"--shuffle\", action=\"store_true\", help=\"Shuffle the data\")\n", + "\n", + " args = parser.parse_args()\n", + " shuffle = args.shuffle\n", + "else:\n", + " shuffle = True" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# load in the treatment groups\n", + "ground_truth = pathlib.Path(\n", + " \"../../4.sc_Morphology_Neural_Network_MLP_Model/MLP_utils/ground_truth.toml\"\n", + ").resolve(strict=True)\n", + "# load in the ground truth\n", + "ground_truth = toml.load(ground_truth)\n", + "apoptosis_ground_truth = ground_truth[\"Apoptosis\"][\"apoptosis_groups_list\"]\n", + "pyroptosis_ground_truth = ground_truth[\"Pyroptosis\"][\"pyroptosis_groups_list\"]\n", + "control_ground_truth = ground_truth[\"Healthy\"][\"healthy_groups_list\"]\n", + "\n", + "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/secretome/\")\n", + "map_out_dir.mkdir(exist_ok=True, parents=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Metadata_WellMetadata_TreatmentActivin A [NSU]AITRL (GITR Ligand) [NSU]Amphiregulin [NSU]Amyloid beta [NSU]APRIL [NSU]BAFF [NSU]BCMA (TNFRSF17) [NSU]BDNF [NSU]...TWEAK [NSU]uPA [NSU]VCAM-1 [NSU]VEGF Receptor 2 (Flk-1) [NSU]VEGF-A (165) [NSU]VEGF-C [NSU]VEGF-D [NSU]VEGFR-1 [NSU]WISP-1 (CCN4) [NSU]XCL1 (Lymphotactin) [NSU]
0B02LPS_0.010_ug_per_ml_DMSO_0.025_%0.7998640.2397810.7714190.2271350.2822810.0779790.5172180.268053...0.4633010.3969020.3850811.0000000.0000000.4301110.5385030.7846950.4684480.237545
1B03LPS_0.010_ug_per_ml_DMSO_0.025_%0.7582050.6612450.7943920.7129200.2363780.2887051.0000000.314184...0.3330560.2566910.3274910.3908660.4064890.4120960.1048300.8129330.5185360.244397
2B04LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...0.1288480.5555800.8237580.2466410.2494010.1092740.8442340.368186...0.4591610.5552210.3574760.3468840.4775530.4276580.6420610.2493800.6277120.318350
3B05LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...0.0619890.5102550.7859980.6156610.0000000.2519620.2983810.492203...0.1186070.3085360.5888990.8283710.4841020.2946340.6736480.2367930.5576340.350429
4B06DMSO_0.100_%_DMSO_0.025_%0.0977100.4616850.2704770.5146950.4792810.2704940.7088490.134432...0.3860630.4698750.3953920.5601290.5045210.4904440.2588340.2383580.5242760.250670
\n", + "

5 rows \u00d7 189 columns

\n", + "
" + ], + "text/plain": [ + " Metadata_Well Metadata_Treatment \\\n", + "0 B02 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", + "1 B03 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", + "2 B04 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", + "3 B05 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", + "4 B06 DMSO_0.100_%_DMSO_0.025_% \n", + "\n", + " Activin A [NSU] AITRL (GITR Ligand) [NSU] Amphiregulin [NSU] \\\n", + "0 0.799864 0.239781 0.771419 \n", + "1 0.758205 0.661245 0.794392 \n", + "2 0.128848 0.555580 0.823758 \n", + "3 0.061989 0.510255 0.785998 \n", + "4 0.097710 0.461685 0.270477 \n", + "\n", + " Amyloid beta [NSU] APRIL [NSU] BAFF [NSU] BCMA (TNFRSF17) [NSU] \\\n", + "0 0.227135 0.282281 0.077979 0.517218 \n", + "1 0.712920 0.236378 0.288705 1.000000 \n", + "2 0.246641 0.249401 0.109274 0.844234 \n", + "3 0.615661 0.000000 0.251962 0.298381 \n", + "4 0.514695 0.479281 0.270494 0.708849 \n", + "\n", + " BDNF [NSU] ... TWEAK [NSU] uPA [NSU] VCAM-1 [NSU] \\\n", + "0 0.268053 ... 0.463301 0.396902 0.385081 \n", + "1 0.314184 ... 0.333056 0.256691 0.327491 \n", + "2 0.368186 ... 0.459161 0.555221 0.357476 \n", + "3 0.492203 ... 0.118607 0.308536 0.588899 \n", + "4 0.134432 ... 0.386063 0.469875 0.395392 \n", + "\n", + " VEGF Receptor 2 (Flk-1) [NSU] VEGF-A (165) [NSU] VEGF-C [NSU] \\\n", + "0 1.000000 0.000000 0.430111 \n", + "1 0.390866 0.406489 0.412096 \n", + "2 0.346884 0.477553 0.427658 \n", + "3 0.828371 0.484102 0.294634 \n", + "4 0.560129 0.504521 0.490444 \n", + "\n", + " VEGF-D [NSU] VEGFR-1 [NSU] WISP-1 (CCN4) [NSU] XCL1 (Lymphotactin) [NSU] \n", + "0 0.538503 0.784695 0.468448 0.237545 \n", + "1 0.104830 0.812933 0.518536 0.244397 \n", + "2 0.642061 0.249380 0.627712 0.318350 \n", + "3 0.673648 0.236793 0.557634 0.350429 \n", + "4 0.258834 0.238358 0.524276 0.250670 \n", + "\n", + "[5 rows x 189 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "agg_data = pathlib.Path(\n", + " \"../../data/PBMC_preprocessed_sc_norm_aggregated_nomic.parquet\"\n", + ").resolve(strict=True)\n", + "df = pd.read_parquet(agg_data)\n", + "# rename oneb_Metadata_Treatment_Dose_Inhibitor_Dose to Metadata_Treatment\n", + "df = df.rename(\n", + " columns={\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\": \"Metadata_Treatment\"}\n", + ")\n", + "df = df.filter(regex=\"Metadata|NSU\")\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# add apoptosis, pyroptosis and healthy columns to dataframe\n", + "df[\"Apoptosis\"] = df.apply(\n", + " lambda row: row[\"Metadata_Treatment\"] in apoptosis_ground_truth,\n", + " axis=1,\n", + ")\n", + "df[\"Pyroptosis\"] = df.apply(\n", + " lambda row: row[\"Metadata_Treatment\"] in pyroptosis_ground_truth,\n", + " axis=1,\n", + ")\n", + "df[\"Control\"] = df.apply(\n", + " lambda row: row[\"Metadata_Treatment\"] in control_ground_truth,\n", + " axis=1,\n", + ")\n", + "\n", + "# merge apoptosis, pyroptosis, and healthy columns into one column\n", + "df[\"Metadata_labels\"] = df.apply(\n", + " lambda row: \"Apoptosis\"\n", + " if row[\"Apoptosis\"]\n", + " else \"Pyroptosis\"\n", + " if row[\"Pyroptosis\"]\n", + " else \"Control\",\n", + " axis=1,\n", + ")\n", + "metadata_labels = df.pop(\"Metadata_labels\")\n", + "df.insert(1, \"Metadata_labels\", metadata_labels)\n", + "# # drop apoptosis, pyroptosis, and healthy columns\n", + "df.drop(columns=[\"Apoptosis\", \"Pyroptosis\", \"Control\"], inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "if shuffle:\n", + " random.seed(0)\n", + " # permutate the data\n", + " for col in df.columns:\n", + " df[col] = np.random.permutation(df[col])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Metadata_WellMetadata_labelsMetadata_TreatmentActivin A [NSU]AITRL (GITR Ligand) [NSU]Amphiregulin [NSU]Amyloid beta [NSU]APRIL [NSU]BAFF [NSU]BCMA (TNFRSF17) [NSU]...uPA [NSU]VCAM-1 [NSU]VEGF Receptor 2 (Flk-1) [NSU]VEGF-A (165) [NSU]VEGF-C [NSU]VEGF-D [NSU]VEGFR-1 [NSU]WISP-1 (CCN4) [NSU]XCL1 (Lymphotactin) [NSU]Metadata_reference_index
0B02PyroptosisLPS_0.100_ug_per_ml_DMSO_0.025_%0.7998640.2397810.7714190.2271350.2822810.0779790.517218...0.3969020.3850811.0000000.0000000.4301110.5385030.7846950.4684480.237545-1
1B03PyroptosisLPS_10.000_ug_per_ml_Disulfiram_1.000_uM0.7582050.6612450.7943920.7129200.2363780.2887051.000000...0.2566910.3274910.3908660.4064890.4120960.1048300.8129330.5185360.244397-1
2B04PyroptosisTopotecan_20.000_nM_DMSO_0.025_%0.1288480.5555800.8237580.2466410.2494010.1092740.844234...0.5552210.3574760.3468840.4775530.4276580.6420610.2493800.6277120.318350-1
3B05PyroptosisFlagellin_0.100_ug_per_ml_DMSO_0.025_%0.0619890.5102550.7859980.6156610.0000000.2519620.298381...0.3085360.5888990.8283710.4841020.2946340.6736480.2367930.5576340.350429-1
4B06ControlMedia0.0977100.4616850.2704770.5146950.4792810.2704940.708849...0.4698750.3953920.5601290.5045210.4904440.2588340.2383580.5242760.250670-1
\n", + "

5 rows \u00d7 191 columns

\n", + "
" + ], + "text/plain": [ + " Metadata_Well Metadata_labels Metadata_Treatment \\\n", + "0 B02 Pyroptosis LPS_0.100_ug_per_ml_DMSO_0.025_% \n", + "1 B03 Pyroptosis LPS_10.000_ug_per_ml_Disulfiram_1.000_uM \n", + "2 B04 Pyroptosis Topotecan_20.000_nM_DMSO_0.025_% \n", + "3 B05 Pyroptosis Flagellin_0.100_ug_per_ml_DMSO_0.025_% \n", + "4 B06 Control Media \n", + "\n", + " Activin A [NSU] AITRL (GITR Ligand) [NSU] Amphiregulin [NSU] \\\n", + "0 0.799864 0.239781 0.771419 \n", + "1 0.758205 0.661245 0.794392 \n", + "2 0.128848 0.555580 0.823758 \n", + "3 0.061989 0.510255 0.785998 \n", + "4 0.097710 0.461685 0.270477 \n", + "\n", + " Amyloid beta [NSU] APRIL [NSU] BAFF [NSU] BCMA (TNFRSF17) [NSU] ... \\\n", + "0 0.227135 0.282281 0.077979 0.517218 ... \n", + "1 0.712920 0.236378 0.288705 1.000000 ... \n", + "2 0.246641 0.249401 0.109274 0.844234 ... \n", + "3 0.615661 0.000000 0.251962 0.298381 ... \n", + "4 0.514695 0.479281 0.270494 0.708849 ... \n", + "\n", + " uPA [NSU] VCAM-1 [NSU] VEGF Receptor 2 (Flk-1) [NSU] VEGF-A (165) [NSU] \\\n", + "0 0.396902 0.385081 1.000000 0.000000 \n", + "1 0.256691 0.327491 0.390866 0.406489 \n", + "2 0.555221 0.357476 0.346884 0.477553 \n", + "3 0.308536 0.588899 0.828371 0.484102 \n", + "4 0.469875 0.395392 0.560129 0.504521 \n", + "\n", + " VEGF-C [NSU] VEGF-D [NSU] VEGFR-1 [NSU] WISP-1 (CCN4) [NSU] \\\n", + "0 0.430111 0.538503 0.784695 0.468448 \n", + "1 0.412096 0.104830 0.812933 0.518536 \n", + "2 0.427658 0.642061 0.249380 0.627712 \n", + "3 0.294634 0.673648 0.236793 0.557634 \n", + "4 0.490444 0.258834 0.238358 0.524276 \n", + "\n", + " XCL1 (Lymphotactin) [NSU] Metadata_reference_index \n", + "0 0.237545 -1 \n", + "1 0.244397 -1 \n", + "2 0.318350 -1 \n", + "3 0.350429 -1 \n", + "4 0.250670 -1 \n", + "\n", + "[5 rows x 191 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reference_col = \"Metadata_reference_index\"\n", + "df_activity = assign_reference_index(\n", + " df,\n", + " \"Metadata_Treatment == 'DMSO_0.100_%_DMSO_0.025_%'\",\n", + " reference_col=reference_col,\n", + " default_value=-1,\n", + ")\n", + "df_activity.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "6d109ae04ebc45be93342eab4e32c965", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/1 [00:00\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Metadata_WellMetadata_labelsMetadata_TreatmentMetadata_reference_indexn_pos_pairsn_total_pairsaverage_precision
0B02PyroptosisLPS_0.100_ug_per_ml_DMSO_0.025_%-108NaN
1B03PyroptosisLPS_10.000_ug_per_ml_Disulfiram_1.000_uM-12100.266667
2B04PyroptosisTopotecan_20.000_nM_DMSO_0.025_%-12100.833333
3B05PyroptosisFlagellin_0.100_ug_per_ml_DMSO_0.025_%-13110.302778
4B06ControlMedia-12100.333333
\n", + "" + ], + "text/plain": [ + " Metadata_Well Metadata_labels Metadata_Treatment \\\n", + "0 B02 Pyroptosis LPS_0.100_ug_per_ml_DMSO_0.025_% \n", + "1 B03 Pyroptosis LPS_10.000_ug_per_ml_Disulfiram_1.000_uM \n", + "2 B04 Pyroptosis Topotecan_20.000_nM_DMSO_0.025_% \n", + "3 B05 Pyroptosis Flagellin_0.100_ug_per_ml_DMSO_0.025_% \n", + "4 B06 Control Media \n", + "\n", + " Metadata_reference_index n_pos_pairs n_total_pairs average_precision \n", + "0 -1 0 8 NaN \n", + "1 -1 2 10 0.266667 \n", + "2 -1 2 10 0.833333 \n", + "3 -1 3 11 0.302778 \n", + "4 -1 2 10 0.333333 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pos_sameby = [\"Metadata_Treatment\", \"Metadata_labels\", reference_col]\n", + "pos_diffby = []\n", + "neg_sameby = []\n", + "neg_diffby = [\"Metadata_Treatment\", reference_col]\n", + "metadata = df_activity.filter(regex=\"Metadata\")\n", + "profiles = df_activity.filter(regex=\"^(?!Metadata)\").values\n", + "\n", + "activity_ap = map.average_precision(\n", + " metadata, profiles, pos_sameby, pos_diffby, neg_sameby, neg_diffby\n", + ")\n", + "\n", + "activity_ap = activity_ap.query(\"Metadata_Treatment != 'DMSO_0.100_%_DMSO_0.025_%'\")\n", + "activity_ap.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2811f073d64e48f599deb4e36ffa867b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/3 [00:00\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Metadata_TreatmentMetadata_labelsMetadata_reference_indexmean_average_precisionindicesp_valuecorrected_p_valuebelow_pbelow_corrected_p-log10(p-value)
0DMSO_0.100_%_DMSO_1.000_%Control-10.750000[46, 57, 68]0.0443200.343276TrueFalse0.464357
1DMSO_0.100_%_Z-VAD-FMK_100.000_uMControl-10.564087[32, 80, 83, 123]0.1996710.343276FalseFalse0.464357
2DMSO_0.100_%_Z-VAD-FMK_30.000_uMPyroptosis-10.513889[7, 78, 103]0.2219140.343276FalseFalse0.464357
3Disulfiram_0.100_uM_DMSO_0.025_%Control-10.200000[86, 118]0.4445270.492845FalseFalse0.307290
4Disulfiram_0.100_uM_DMSO_0.025_%Pyroptosis-10.333333[58, 94]0.2221200.343276FalseFalse0.464357
\n", + "" + ], + "text/plain": [ + " Metadata_Treatment Metadata_labels \\\n", + "0 DMSO_0.100_%_DMSO_1.000_% Control \n", + "1 DMSO_0.100_%_Z-VAD-FMK_100.000_uM Control \n", + "2 DMSO_0.100_%_Z-VAD-FMK_30.000_uM Pyroptosis \n", + "3 Disulfiram_0.100_uM_DMSO_0.025_% Control \n", + "4 Disulfiram_0.100_uM_DMSO_0.025_% Pyroptosis \n", + "\n", + " Metadata_reference_index mean_average_precision indices \\\n", + "0 -1 0.750000 [46, 57, 68] \n", + "1 -1 0.564087 [32, 80, 83, 123] \n", + "2 -1 0.513889 [7, 78, 103] \n", + "3 -1 0.200000 [86, 118] \n", + "4 -1 0.333333 [58, 94] \n", + "\n", + " p_value corrected_p_value below_p below_corrected_p -log10(p-value) \n", + "0 0.044320 0.343276 True False 0.464357 \n", + "1 0.199671 0.343276 False False 0.464357 \n", + "2 0.221914 0.343276 False False 0.464357 \n", + "3 0.444527 0.492845 False False 0.307290 \n", + "4 0.222120 0.343276 False False 0.464357 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "activity_map = map.mean_average_precision(\n", + " activity_ap, pos_sameby, null_size=1000000, threshold=0.05, seed=0\n", + ")\n", + "activity_map[\"-log10(p-value)\"] = -activity_map[\"corrected_p_value\"].apply(np.log10)\n", + "# flatten the multi-index columns to make it easier to work with\n", + "activity_map.reset_index(inplace=True)\n", + "activity_map.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "if shuffle:\n", + " activity_map.to_parquet(map_out_dir / \"activity_map_shuffled.parquet\")\n", + "else:\n", + " activity_map.to_parquet(map_out_dir / \"activity_map.parquet\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "map", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.2" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/9.mAP/notebooks/2.generate_map_scores_secretome.ipynb b/9.mAP/notebooks/2.generate_map_scores_secretome.ipynb deleted file mode 100644 index dc7bf82c6..000000000 --- a/9.mAP/notebooks/2.generate_map_scores_secretome.ipynb +++ /dev/null @@ -1,1228 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import itertools\n", - "import logging\n", - "import pathlib\n", - "import sys\n", - "from typing import Optional\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "import toml\n", - "from copairs.map import run_pipeline\n", - "from pycytominer import feature_select\n", - "\n", - "# imports src\n", - "sys.path.append(\"../\")\n", - "from src import utils\n", - "\n", - "# setting up logger\n", - "logging.basicConfig(\n", - " filename=\"map_analysis_testing.log\",\n", - " level=logging.DEBUG,\n", - " format=\"%(levelname)s:%(asctime)s:%(name)s:%(message)s\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Helper functions\n", - "Set of helper functions to help out throughout the notebook" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "## Helper function\n", - "\n", - "\n", - "def shuffle_meta_labels(\n", - " dataset: pd.DataFrame, target_col: str, seed: Optional[int] = 0\n", - ") -> pd.DataFrame:\n", - " \"\"\"shuffles labels or values within a single selected column\n", - "\n", - " Parameters\n", - " ----------\n", - " dataset : pd.DataFrame\n", - " dataframe containing the dataset\n", - "\n", - " target_col : str\n", - " Column to select in order to conduct the shuffling\n", - "\n", - " seed : int\n", - " setting random seed\n", - "\n", - " Returns\n", - " -------\n", - " pd.DataFrame\n", - " shuffled dataset\n", - "\n", - " Raises\n", - " ------\n", - " TypeError\n", - " raised if incorrect types are provided\n", - " \"\"\"\n", - " # setting seed\n", - " np.random.seed(seed)\n", - "\n", - " # type checking\n", - " if not isinstance(target_col, str):\n", - " raise TypeError(\"'target_col' must be a string type\")\n", - " if not isinstance(dataset, pd.DataFrame):\n", - " raise TypeError(\"'dataset' must be a pandas dataframe\")\n", - "\n", - " # selecting column, shuffle values within column, add to dataframe\n", - " dataset[target_col] = np.random.permutation(dataset[target_col].values)\n", - " return dataset\n", - "\n", - "\n", - "def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.array:\n", - " \"\"\"suffles all values within feature space\n", - "\n", - " Parameters\n", - " ----------\n", - " feature_vals : np.array\n", - " shuffled\n", - "\n", - " seed : Optional[int]\n", - " setting random seed\n", - "\n", - " Returns\n", - " -------\n", - " np.array\n", - " Returns shuffled values within the feature space\n", - "\n", - " Raises\n", - " ------\n", - " TypeError\n", - " Raised if a numpy array is not provided\n", - " \"\"\"\n", - " # setting seed\n", - " np.random.seed(seed)\n", - "\n", - " # shuffle given array\n", - " if not isinstance(feature_vals, np.ndarray):\n", - " raise TypeError(\"'feature_vals' must be a numpy array\")\n", - " if feature_vals.ndim != 2:\n", - " raise TypeError(\"'feature_vals' must be a 2x2 matrix\")\n", - "\n", - " # creating a copy for feature vales to prevent overwriting of global variables\n", - " feature_vals = np.copy(feature_vals)\n", - "\n", - " # shuffling feature space\n", - " n_cols = feature_vals.shape[1]\n", - " for col_idx in range(0, n_cols):\n", - " # selecting column, shuffle, and update:\n", - " feature_vals[:, col_idx] = np.random.permutation(feature_vals[:, col_idx])\n", - "\n", - " return feature_vals" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setting up Paths and loading data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# load in the treatment groups\n", - "ground_truth = pathlib.Path(\n", - " \"../../4.sc_Morphology_Neural_Network_MLP_Model/MLP_utils/ground_truth.toml\"\n", - ").resolve(strict=True)\n", - "# load in the ground truth\n", - "ground_truth = toml.load(ground_truth)\n", - "apoptosis_ground_truth = ground_truth[\"Apoptosis\"][\"apoptosis_groups_list\"]\n", - "pyroptosis_ground_truth = ground_truth[\"Pyroptosis\"][\"pyroptosis_groups_list\"]\n", - "control_ground_truth = ground_truth[\"Healthy\"][\"healthy_groups_list\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "single_cell_data = pathlib.Path(\n", - " f\"../../data/PBMC_preprocessed_sc_norm_aggregated_nomic.parquet\"\n", - ").resolve(strict=True)\n", - "df = pd.read_parquet(single_cell_data)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# out paths\n", - "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/secretome/\")\n", - "map_out_dir.mkdir(exist_ok=True, parents=True)\n", - "\n", - "# regular data output\n", - "# saving to csv\n", - "regular_feat_map_path = pathlib.Path(map_out_dir / \"mAP_scores_regular_class.csv\")\n", - "\n", - "# shuffled data output\n", - "shuffled_feat_map_path = pathlib.Path(map_out_dir / \"mAP_scores_shuffled_class.csv\")\n", - "\n", - "# shuffled feature space output\n", - "shuffled_feat_space_map_path = pathlib.Path(\n", - " map_out_dir / \"mAP_scores_shuffled_feature_space_class.csv\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Clean up data" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# add apoptosis, pyroptosis and healthy columns to dataframe\n", - "df[\"Apoptosis\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in apoptosis_ground_truth,\n", - " axis=1,\n", - ")\n", - "df[\"Pyroptosis\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in pyroptosis_ground_truth,\n", - " axis=1,\n", - ")\n", - "df[\"Control\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in control_ground_truth,\n", - " axis=1,\n", - ")\n", - "\n", - "# merge apoptosis, pyroptosis, and healthy columns into one column\n", - "df[\"Metadata_labels\"] = df.apply(\n", - " lambda row: \"Apoptosis\"\n", - " if row[\"Apoptosis\"]\n", - " else \"Pyroptosis\"\n", - " if row[\"Pyroptosis\"]\n", - " else \"Control\",\n", - " axis=1,\n", - ")\n", - "# # drop apoptosis, pyroptosis, and healthy columns\n", - "df.drop(columns=[\"Apoptosis\", \"Pyroptosis\", \"Control\"], inplace=True)\n", - "df.drop(columns=[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"], inplace=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellActivin A [NSU]AITRL (GITR Ligand) [NSU]Amphiregulin [NSU]Amyloid beta [NSU]APRIL [NSU]BAFF [NSU]BCMA (TNFRSF17) [NSU]BDNF [NSU]BMP2 [NSU]...uPA [NSU]VCAM-1 [NSU]VEGF Receptor 2 (Flk-1) [NSU]VEGF-A (165) [NSU]VEGF-C [NSU]VEGF-D [NSU]VEGFR-1 [NSU]WISP-1 (CCN4) [NSU]XCL1 (Lymphotactin) [NSU]Metadata_labels
0B020.7998640.2397810.7714190.2271350.2822810.0779790.5172180.2680530.205627...0.3969020.3850811.0000000.0000000.4301110.5385030.7846950.4684480.237545Pyroptosis
1B030.7582050.6612450.7943920.7129200.2363780.2887051.0000000.3141840.580188...0.2566910.3274910.3908660.4064890.4120960.1048300.8129330.5185360.244397Pyroptosis
2B040.1288480.5555800.8237580.2466410.2494010.1092740.8442340.3681860.506013...0.5552210.3574760.3468840.4775530.4276580.6420610.2493800.6277120.318350Pyroptosis
3B050.0619890.5102550.7859980.6156610.0000000.2519620.2983810.4922030.428714...0.3085360.5888990.8283710.4841020.2946340.6736480.2367930.5576340.350429Pyroptosis
4B060.0977100.4616850.2704770.5146950.4792810.2704940.7088490.1344320.350986...0.4698750.3953920.5601290.5045210.4904440.2588340.2383580.5242760.250670Control
\n", - "

5 rows \u00d7 189 columns

\n", - "
" - ], - "text/plain": [ - " Metadata_Well Activin A [NSU] AITRL (GITR Ligand) [NSU] \\\n", - "0 B02 0.799864 0.239781 \n", - "1 B03 0.758205 0.661245 \n", - "2 B04 0.128848 0.555580 \n", - "3 B05 0.061989 0.510255 \n", - "4 B06 0.097710 0.461685 \n", - "\n", - " Amphiregulin [NSU] Amyloid beta [NSU] APRIL [NSU] BAFF [NSU] \\\n", - "0 0.771419 0.227135 0.282281 0.077979 \n", - "1 0.794392 0.712920 0.236378 0.288705 \n", - "2 0.823758 0.246641 0.249401 0.109274 \n", - "3 0.785998 0.615661 0.000000 0.251962 \n", - "4 0.270477 0.514695 0.479281 0.270494 \n", - "\n", - " BCMA (TNFRSF17) [NSU] BDNF [NSU] BMP2 [NSU] ... uPA [NSU] \\\n", - "0 0.517218 0.268053 0.205627 ... 0.396902 \n", - "1 1.000000 0.314184 0.580188 ... 0.256691 \n", - "2 0.844234 0.368186 0.506013 ... 0.555221 \n", - "3 0.298381 0.492203 0.428714 ... 0.308536 \n", - "4 0.708849 0.134432 0.350986 ... 0.469875 \n", - "\n", - " VCAM-1 [NSU] VEGF Receptor 2 (Flk-1) [NSU] VEGF-A (165) [NSU] \\\n", - "0 0.385081 1.000000 0.000000 \n", - "1 0.327491 0.390866 0.406489 \n", - "2 0.357476 0.346884 0.477553 \n", - "3 0.588899 0.828371 0.484102 \n", - "4 0.395392 0.560129 0.504521 \n", - "\n", - " VEGF-C [NSU] VEGF-D [NSU] VEGFR-1 [NSU] WISP-1 (CCN4) [NSU] \\\n", - "0 0.430111 0.538503 0.784695 0.468448 \n", - "1 0.412096 0.104830 0.812933 0.518536 \n", - "2 0.427658 0.642061 0.249380 0.627712 \n", - "3 0.294634 0.673648 0.236793 0.557634 \n", - "4 0.490444 0.258834 0.238358 0.524276 \n", - "\n", - " XCL1 (Lymphotactin) [NSU] Metadata_labels \n", - "0 0.237545 Pyroptosis \n", - "1 0.244397 Pyroptosis \n", - "2 0.318350 Pyroptosis \n", - "3 0.350429 Pyroptosis \n", - "4 0.250670 Control \n", - "\n", - "[5 rows x 189 columns]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# keep columns that contain Metdata and ['NSU']\n", - "df = df.filter(regex=\"Metadata|NSU\")\n", - "df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# output directories\n", - "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/\")\n", - "map_out_dir.mkdir(parents=True, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP Pipeline Parameters" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The null size needs to be determined for the mAP pipeline. This is the size of the null class that is used to determine the mAP score." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "65" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tmp = (\n", - " df.groupby([\"Metadata_labels\"])\n", - " .count()\n", - " .reset_index()[[\"Metadata_Well\", \"Metadata_labels\"]]\n", - ")\n", - "# get the Pyroptosis number of Metadata_Well\n", - "Pyroptosis_count = tmp[tmp[\"Metadata_labels\"] == \"Pyroptosis\"][\"Metadata_Well\"].values[\n", - " 0\n", - "]\n", - "Pyroptosis_count" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "pos_sameby = [\n", - " \"Metadata_labels\",\n", - "]\n", - "pos_diffby = [\"Metadata_Well\"]\n", - "\n", - "neg_sameby = []\n", - "neg_diffby = [\"Metadata_labels\"]\n", - "\n", - "null_size = Pyroptosis_count\n", - "batch_size = 1\n", - "\n", - "# number of resampling\n", - "n_resamples = 10" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP analysis for non-shuffled data" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "# generate the permutations of cell death labels via itertools\n", - "pos_samby_permutations = list(itertools.combinations(df[\"Metadata_labels\"].unique(), 2))" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "results_df = pd.DataFrame(\n", - " columns=[\n", - " \"Metadata_Well\",\n", - " \"Metadata_labels\",\n", - " \"average_precision\",\n", - " \"p_value\",\n", - " \"n_pos_pairs\",\n", - " \"n_total_pairs\",\n", - " \"shuffled\",\n", - " \"comparison\",\n", - " ]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "1d792ab171334585a30eb2f126133b69", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/4930 [00:00\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparison
0B06Control0.9666630.01515275.083.0non-shuffledControl_vs_Apoptosis
1B07Control0.9414570.09090975.083.0non-shuffledControl_vs_Apoptosis
2B12Control0.9624840.01515275.083.0non-shuffledControl_vs_Apoptosis
3C06Control0.9641830.01515275.083.0non-shuffledControl_vs_Apoptosis
4C07Control0.9709790.01515275.083.0non-shuffledControl_vs_Apoptosis
\n", - "" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 B06 Control 0.966663 0.015152 75.0 \n", - "1 B07 Control 0.941457 0.090909 75.0 \n", - "2 B12 Control 0.962484 0.015152 75.0 \n", - "3 C06 Control 0.964183 0.015152 75.0 \n", - "4 C07 Control 0.970979 0.015152 75.0 \n", - "\n", - " n_total_pairs shuffled comparison \n", - "0 83.0 non-shuffled Control_vs_Apoptosis \n", - "1 83.0 non-shuffled Control_vs_Apoptosis \n", - "2 83.0 non-shuffled Control_vs_Apoptosis \n", - "3 83.0 non-shuffled Control_vs_Apoptosis \n", - "4 83.0 non-shuffled Control_vs_Apoptosis " - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "for i in pos_samby_permutations:\n", - " # print(i)\n", - " tmp = df.copy()\n", - " # get only the rows with the current permutation\n", - " tmp = tmp[tmp[\"Metadata_labels\"].isin(i)]\n", - " # This will generated 100 values [0..100] as seed values\n", - " # This will occur per phenotype\n", - "\n", - " # spliting metadata and raw feature values\n", - " logging.info(\"splitting data set into metadata and raw feature values\")\n", - " df_meta, df_feats = utils.split_data(tmp)\n", - " df_feats = np.array(df_feats)\n", - "\n", - " # execute pipeline on negative control with training dataset with cp features\n", - " try:\n", - " # execute pipeline on negative control with trianing dataset with cp features\n", - "\n", - " logging.info(f\"Running pipeline on CP features using phenotype\")\n", - " result = run_pipeline(\n", - " meta=df_meta,\n", - " feats=df_feats,\n", - " pos_sameby=pos_sameby,\n", - " pos_diffby=pos_diffby,\n", - " neg_sameby=neg_sameby,\n", - " neg_diffby=neg_diffby,\n", - " batch_size=batch_size,\n", - " null_size=null_size,\n", - " )\n", - "\n", - " # adding columns\n", - " result[\"shuffled\"] = \"non-shuffled\"\n", - " result[\"comparison\"] = \"_vs_\".join(i)\n", - "\n", - " except ZeroDivisionError as e:\n", - " logging.warning(f\"{e} captured on phenotye:. Skipping\")\n", - "\n", - " # concatenating all datasets\n", - " results_df = pd.concat([results_df, result], ignore_index=True)\n", - "# concatenating all datasets\n", - "results_df.to_csv(regular_feat_map_path, index=False)\n", - "result.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP analysis for shuffled data (Feature space)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "results_df = pd.DataFrame(\n", - " columns=[\n", - " \"Metadata_Well\",\n", - " \"Metadata_labels\",\n", - " \"average_precision\",\n", - " \"p_value\",\n", - " \"n_pos_pairs\",\n", - " \"n_total_pairs\",\n", - " \"shuffled\",\n", - " \"comparison\",\n", - " ]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "aaaeee5096f14af88d4b32e5e4fc7bf8", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/4930 [00:00\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparison
0B02Pyroptosis0.3876111.00000064.0140.0shuffled_baselinePyroptosis_vs_Control
1B03Pyroptosis0.4555590.74242464.0140.0shuffled_baselinePyroptosis_vs_Control
2B04Pyroptosis0.4940000.42424264.0140.0shuffled_baselinePyroptosis_vs_Control
3B05Pyroptosis0.4839160.46969764.0140.0shuffled_baselinePyroptosis_vs_Control
4B06Control0.5385820.65151575.0140.0shuffled_baselinePyroptosis_vs_Control
\n", - "" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 B02 Pyroptosis 0.387611 1.000000 64.0 \n", - "1 B03 Pyroptosis 0.455559 0.742424 64.0 \n", - "2 B04 Pyroptosis 0.494000 0.424242 64.0 \n", - "3 B05 Pyroptosis 0.483916 0.469697 64.0 \n", - "4 B06 Control 0.538582 0.651515 75.0 \n", - "\n", - " n_total_pairs shuffled comparison \n", - "0 140.0 shuffled_baseline Pyroptosis_vs_Control \n", - "1 140.0 shuffled_baseline Pyroptosis_vs_Control \n", - "2 140.0 shuffled_baseline Pyroptosis_vs_Control \n", - "3 140.0 shuffled_baseline Pyroptosis_vs_Control \n", - "4 140.0 shuffled_baseline Pyroptosis_vs_Control " - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "for i in pos_samby_permutations:\n", - " # print(i)\n", - " tmp = df.copy()\n", - " # get only the rows with the current permutation\n", - " tmp = tmp[tmp[\"Metadata_labels\"].isin(i)]\n", - " # This will generated 100 values [0..100] as seed values\n", - " seed = np.random.randint(0, 100)\n", - "\n", - " # split the shuffled dataset\n", - " # spliting metadata and raw feature values\n", - " logging.info(\"splitting shuffled data set into metadata and raw feature values\")\n", - " (\n", - " df_meta,\n", - " df_feats,\n", - " ) = utils.split_data(tmp)\n", - "\n", - " df_feats = np.array(df_feats)\n", - "\n", - " # shuffling the features, this will overwrite the generated feature space from above with the shuffled one\n", - " df_feats = shuffle_features(feature_vals=df_feats, seed=seed)\n", - "\n", - " try:\n", - " # execute pipeline on negative control with trianing dataset with cp features\n", - " logging.info(\n", - " f\"Running pipeline on CP features using phenotype, feature space is shuffled\"\n", - " )\n", - " shuffled_feat_map = run_pipeline(\n", - " meta=df_meta,\n", - " feats=df_feats,\n", - " pos_sameby=pos_sameby,\n", - " pos_diffby=pos_diffby,\n", - " neg_sameby=neg_sameby,\n", - " neg_diffby=neg_diffby,\n", - " batch_size=batch_size,\n", - " null_size=null_size,\n", - " )\n", - "\n", - " # adding shuffle label column\n", - " shuffled_feat_map[\"shuffled\"] = \"shuffled\"\n", - " shuffled_feat_map[\"comparison\"] = \"_vs_\".join(i)\n", - "\n", - " except ZeroDivisionError as e:\n", - " logging.warning(f\"{e} captured on phenotype: Skipping\")\n", - "\n", - " # concatenating all datasets\n", - " results_df = pd.concat([results_df, shuffled_feat_map], ignore_index=True)\n", - " # saving to csv\n", - "\n", - "# saving to csv\n", - "results_df.to_csv(shuffled_feat_space_map_path, index=False)\n", - "results_df.head()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "map", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.mAP/notebooks/2.visualize_map_scores.ipynb b/9.mAP/notebooks/2.visualize_map_scores.ipynb new file mode 100644 index 000000000..822fcf8ee --- /dev/null +++ b/9.mAP/notebooks/2.visualize_map_scores.ipynb @@ -0,0 +1,643 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [], + "source": [ + "suppressPackageStartupMessages(suppressWarnings(library(ggplot2)))\n", + "suppressPackageStartupMessages(suppressWarnings(library(RColorBrewer)))\n", + "suppressPackageStartupMessages(suppressWarnings(library(dplyr)))\n", + "suppressPackageStartupMessages(suppressWarnings(library(tidyr)))\n", + "suppressPackageStartupMessages(suppressWarnings(library(arrow)))\n", + "source(\"../../figures/utils/figure_themes.r\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 6 \u00d7 5
Metadata_TreatmentMetadata_labelsmean_average_precisionshuffleddata_type
<chr><chr><dbl><chr><chr>
DMSO_0.100_%_DMSO_1.000_% Control0.9125000Non-shuffledMorphology
DMSO_0.100_%_Z-VAD-FMK_100.000_uMControl0.9097222Non-shuffledMorphology
DMSO_0.100_%_Z-VAD-FMK_30.000_uM Control0.8750000Non-shuffledMorphology
Disulfiram_0.100_uM_DMSO_0.025_% Control0.4178662Non-shuffledMorphology
Disulfiram_1.000_uM_DMSO_0.025_% Control0.4313672Non-shuffledMorphology
Disulfiram_2.500_uM_DMSO_0.025_% Control0.4289863Non-shuffledMorphology
\n" + ], + "text/latex": [ + "A tibble: 6 \u00d7 5\n", + "\\begin{tabular}{lllll}\n", + " Metadata\\_Treatment & Metadata\\_labels & mean\\_average\\_precision & shuffled & data\\_type\\\\\n", + " & & & & \\\\\n", + "\\hline\n", + "\t DMSO\\_0.100\\_\\%\\_DMSO\\_1.000\\_\\% & Control & 0.9125000 & Non-shuffled & Morphology\\\\\n", + "\t DMSO\\_0.100\\_\\%\\_Z-VAD-FMK\\_100.000\\_uM & Control & 0.9097222 & Non-shuffled & Morphology\\\\\n", + "\t DMSO\\_0.100\\_\\%\\_Z-VAD-FMK\\_30.000\\_uM & Control & 0.8750000 & Non-shuffled & Morphology\\\\\n", + "\t Disulfiram\\_0.100\\_uM\\_DMSO\\_0.025\\_\\% & Control & 0.4178662 & Non-shuffled & Morphology\\\\\n", + "\t Disulfiram\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & Control & 0.4313672 & Non-shuffled & Morphology\\\\\n", + "\t Disulfiram\\_2.500\\_uM\\_DMSO\\_0.025\\_\\% & Control & 0.4289863 & Non-shuffled & Morphology\\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "A tibble: 6 \u00d7 5\n", + "\n", + "| Metadata_Treatment <chr> | Metadata_labels <chr> | mean_average_precision <dbl> | shuffled <chr> | data_type <chr> |\n", + "|---|---|---|---|---|\n", + "| DMSO_0.100_%_DMSO_1.000_% | Control | 0.9125000 | Non-shuffled | Morphology |\n", + "| DMSO_0.100_%_Z-VAD-FMK_100.000_uM | Control | 0.9097222 | Non-shuffled | Morphology |\n", + "| DMSO_0.100_%_Z-VAD-FMK_30.000_uM | Control | 0.8750000 | Non-shuffled | Morphology |\n", + "| Disulfiram_0.100_uM_DMSO_0.025_% | Control | 0.4178662 | Non-shuffled | Morphology |\n", + "| Disulfiram_1.000_uM_DMSO_0.025_% | Control | 0.4313672 | Non-shuffled | Morphology |\n", + "| Disulfiram_2.500_uM_DMSO_0.025_% | Control | 0.4289863 | Non-shuffled | Morphology |\n", + "\n" + ], + "text/plain": [ + " Metadata_Treatment Metadata_labels mean_average_precision\n", + "1 DMSO_0.100_%_DMSO_1.000_% Control 0.9125000 \n", + "2 DMSO_0.100_%_Z-VAD-FMK_100.000_uM Control 0.9097222 \n", + "3 DMSO_0.100_%_Z-VAD-FMK_30.000_uM Control 0.8750000 \n", + "4 Disulfiram_0.100_uM_DMSO_0.025_% Control 0.4178662 \n", + "5 Disulfiram_1.000_uM_DMSO_0.025_% Control 0.4313672 \n", + "6 Disulfiram_2.500_uM_DMSO_0.025_% Control 0.4289863 \n", + " shuffled data_type \n", + "1 Non-shuffled Morphology\n", + "2 Non-shuffled Morphology\n", + "3 Non-shuffled Morphology\n", + "4 Non-shuffled Morphology\n", + "5 Non-shuffled Morphology\n", + "6 Non-shuffled Morphology" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# set path to the data morphology\n", + "\n", + "morphology_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"activity_map.parquet\")\n", + "shuffled_morphology_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"activity_map_shuffled.parquet\")\n", + "# set path to the secretome data\n", + "\n", + "secretome_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"activity_map.parquet\")\n", + "shuffled_secretome_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"activity_map_shuffled.parquet\")\n", + "\n", + "df_morphology <- arrow::read_parquet(morphology_path) %>% \n", + " dplyr::mutate(shuffled = \"Non-shuffled\") %>%\n", + " dplyr::mutate(data_type = \"Morphology\") %>%\n", + " # rename the mean_average_precision column to specifcy morphology\n", + " # drop unnecessary columns\n", + " dplyr::select(-c(\"Metadata_reference_index\", \"indices\", \"p_value\", \"corrected_p_value\", \"below_p\", \"below_corrected_p\",\"-log10(p-value)\"))\t\n", + "\n", + "df_shuffled_morphology <- arrow::read_parquet(shuffled_morphology_path) %>%\n", + " dplyr::mutate(shuffled = \"Shuffled\") %>%\n", + " dplyr::mutate(data_type = \"Morphology\") %>%\n", + " # rename the mean_average_precision column to specifcy morphology\n", + " dplyr::select(-c(\"Metadata_reference_index\", \"indices\", \"p_value\", \"corrected_p_value\", \"below_p\", \"below_corrected_p\",\"-log10(p-value)\"))\t\n", + "\n", + "\n", + "df_secretome <- arrow::read_parquet(secretome_path) %>%\n", + " dplyr::mutate(shuffled = \"Non-shuffled\") %>%\n", + " dplyr::mutate(data_type = \"Secretome\") %>%\n", + " # rename the mean_average_precision column to specifcy secretome\n", + " dplyr::select(-c(\"Metadata_reference_index\", \"indices\", \"p_value\", \"corrected_p_value\", \"below_p\", \"below_corrected_p\",\"-log10(p-value)\"))\t\n", + "\n", + "\n", + "df_shuffled_secretome <- arrow::read_parquet(shuffled_secretome_path) %>%\n", + " dplyr::mutate(shuffled = \"Shuffled\") %>%\n", + " dplyr::mutate(data_type = \"Secretome\") %>%\n", + " # rename the mean_average_precision column to specifcy secretome\n", + " dplyr::select(-c(\"Metadata_reference_index\", \"indices\", \"p_value\", \"corrected_p_value\", \"below_p\", \"below_corrected_p\",\"-log10(p-value)\"))\t\n", + "\n", + "df <- dplyr::bind_rows(df_morphology, df_shuffled_morphology, df_secretome, df_shuffled_secretome)\n", + "head(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [], + "source": [ + "# split out the morphology and secretome data\n", + "morphology_data <- df %>% dplyr::filter(data_type == \"Morphology\")\n", + "secretome_data <- df %>% dplyr::filter(data_type == \"Secretome\")\n", + "# rename the mean_average_precision column to specifcy morphology\n", + "morphology_data <- morphology_data %>% dplyr::rename(mAP_moprhology = mean_average_precision)\n", + "secretome_data <- secretome_data %>% dplyr::rename(mAP_secretome = mean_average_precision)\n", + "# drop the data_type column\n", + "morphology_data <- morphology_data %>% dplyr::select(-data_type)\n", + "secretome_data <- secretome_data %>% dplyr::select(-data_type)\n", + "# merge the data together to plot \n", + "df <- merge(morphology_data, secretome_data,by = c(\"Metadata_Treatment\", \"Metadata_labels\", \"shuffled\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [], + "source": [ + "levels_list <- c(\n", + " 'Media',\n", + " 'DMSO_0.100_%_DMSO_0.025_%',\n", + " 'DMSO_0.100_%_DMSO_1.000_%',\n", + " 'DMSO_0.100_%_Z-VAD-FMK_30.000_uM',\n", + " 'DMSO_0.100_%_Z-VAD-FMK_100.000_uM',\n", + "\n", + " 'Disulfiram_0.100_uM_DMSO_0.025_%',\n", + " 'Disulfiram_1.000_uM_DMSO_0.025_%',\n", + " 'Disulfiram_2.500_uM_DMSO_0.025_%',\n", + " \n", + " 'Flagellin_0.100_ug_per_ml_DMSO_0.025_%',\n", + " 'Flagellin_1.000_ug_per_ml_DMSO_0.025_%',\n", + " 'Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM',\n", + " \n", + " 'LPS_0.010_ug_per_ml_DMSO_0.025_%',\n", + " 'LPS_0.100_ug_per_ml_DMSO_0.025_%',\n", + " 'LPS_1.000_ug_per_ml_DMSO_0.025_%',\n", + "\n", + " 'LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%',\n", + " 'LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%',\n", + " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%',\n", + " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM',\n", + " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM',\n", + "\n", + " 'LPS_10.000_ug_per_ml_DMSO_0.025_%',\n", + " 'LPS_10.000_ug_per_ml_Disulfiram_0.100_uM',\n", + " 'LPS_10.000_ug_per_ml_Disulfiram_1.000_uM',\n", + " 'LPS_10.000_ug_per_ml_Disulfiram_2.500_uM',\n", + " 'LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM',\n", + " \n", + " 'LPS_100.000_ug_per_ml_DMSO_0.025_%',\n", + " 'LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%',\n", + " 'LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%',\n", + " 'LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%',\n", + "\n", + " 'H2O2_100.000_nM_DMSO_0.025_%',\n", + " 'H2O2_100.000_uM_DMSO_0.025_%',\n", + " 'H2O2_100.000_uM_Disulfiram_1.000_uM',\n", + " 'H2O2_100.000_uM_Z-VAD-FMK_100.000_uM',\n", + " 'Thapsigargin_1.000_uM_DMSO_0.025_%',\n", + " 'Thapsigargin_10.000_uM_DMSO_0.025_%',\n", + "\n", + " 'Topotecan_5.000_nM_DMSO_0.025_%', \n", + " 'Topotecan_10.000_nM_DMSO_0.025_%',\n", + " 'Topotecan_20.000_nM_DMSO_0.025_%'\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Clean the class data" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [], + "source": [ + "df$Metadata_labels <- factor(df$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", + "df$Metadata_Treatment <- factor(df$Metadata_Treatment, levels =levels_list)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## mAP Scatter compare plot treatemnts\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 420, + "width": 420 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "# scatter plot\n", + "scatter_compare_treatment <- (\n", + " ggplot(df, aes(x=mAP_moprhology, y=mAP_secretome, col = Metadata_labels, shape=shuffled))\n", + " + geom_point(size=3, alpha=0.5)\n", + " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", + " + theme_bw()\n", + " + ggtitle(\"Comparison of mAP scores\")\n", + " + ylim(0,1)\n", + " + xlim(0,1)\n", + " # Change the legend title\n", + " # change the legend shape\n", + " + scale_shape_manual(\n", + " name=\"Shuffle type\",\n", + " labels=c(\n", + " \"Non-shuffled\", \n", + " \"Shuffled features\", \n", + " \"Shuffled phenotypes\"\n", + " ),\n", + " values=c(19, 17, 15)\n", + " )\n", + " + scale_color_manual(\n", + " name=\"Class\",\n", + " labels=c(\n", + " \"Control\", \n", + " \"Apoptosis\", \n", + " \"Pyroptosis\"\n", + " ),\n", + " values=c(\n", + " brewer.pal(3, \"Dark2\")[2],\n", + " brewer.pal(3, \"Dark2\")[1],\n", + " brewer.pal(3, \"Dark2\")[3]\n", + " )\n", + ")\n", + " + figure_theme\n", + " # add y = x line\n", + " + geom_abline(intercept = 0, slope = 1, linetype=\"dashed\", color = \"black\")\n", + ")\n", + "scatter_compare_treatment" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A data.frame: 6 \u00d7 7
Metadata_TreatmentinducerinhibitorMetadata_labelsshuffledmAP_moprhologymAP_secretome
<chr><fct><fct><fct><chr><dbl><dbl>
1Disulfiram 0.1 uM - DMSO 0.025%Disulfiram 0.1 uMDMSO 0.025%Control Non-shuffled0.41786620.4012085
2Disulfiram 0.1 uM - DMSO 0.025%Disulfiram 0.1 uMDMSO 0.025%Control Shuffled 0.29166670.6666667
3Disulfiram 1.0 uM - DMSO 0.025%Disulfiram 1.0 uMDMSO 0.025%Control Non-shuffled0.43136720.5312500
4Disulfiram 1.0 uM - DMSO 0.025%Disulfiram 1.0 uMDMSO 0.025%PyroptosisShuffled 0.33333330.1458333
5Disulfiram 2.5 uM - DMSO 0.025%Disulfiram 2.5 uMDMSO 0.025%Control Non-shuffled0.42898630.5597222
6DMSO 0.1% - DMSO 1.0% DMSO 0.1% DMSO 1.0% Control Non-shuffled0.91250000.8916667
\n" + ], + "text/latex": [ + "A data.frame: 6 \u00d7 7\n", + "\\begin{tabular}{r|lllllll}\n", + " & Metadata\\_Treatment & inducer & inhibitor & Metadata\\_labels & shuffled & mAP\\_moprhology & mAP\\_secretome\\\\\n", + " & & & & & & & \\\\\n", + "\\hline\n", + "\t1 & Disulfiram 0.1 uM - DMSO 0.025\\% & Disulfiram 0.1 uM & DMSO 0.025\\% & Control & Non-shuffled & 0.4178662 & 0.4012085\\\\\n", + "\t2 & Disulfiram 0.1 uM - DMSO 0.025\\% & Disulfiram 0.1 uM & DMSO 0.025\\% & Control & Shuffled & 0.2916667 & 0.6666667\\\\\n", + "\t3 & Disulfiram 1.0 uM - DMSO 0.025\\% & Disulfiram 1.0 uM & DMSO 0.025\\% & Control & Non-shuffled & 0.4313672 & 0.5312500\\\\\n", + "\t4 & Disulfiram 1.0 uM - DMSO 0.025\\% & Disulfiram 1.0 uM & DMSO 0.025\\% & Pyroptosis & Shuffled & 0.3333333 & 0.1458333\\\\\n", + "\t5 & Disulfiram 2.5 uM - DMSO 0.025\\% & Disulfiram 2.5 uM & DMSO 0.025\\% & Control & Non-shuffled & 0.4289863 & 0.5597222\\\\\n", + "\t6 & DMSO 0.1\\% - DMSO 1.0\\% & DMSO 0.1\\% & DMSO 1.0\\% & Control & Non-shuffled & 0.9125000 & 0.8916667\\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "A data.frame: 6 \u00d7 7\n", + "\n", + "| | Metadata_Treatment <chr> | inducer <fct> | inhibitor <fct> | Metadata_labels <fct> | shuffled <chr> | mAP_moprhology <dbl> | mAP_secretome <dbl> |\n", + "|---|---|---|---|---|---|---|---|\n", + "| 1 | Disulfiram 0.1 uM - DMSO 0.025% | Disulfiram 0.1 uM | DMSO 0.025% | Control | Non-shuffled | 0.4178662 | 0.4012085 |\n", + "| 2 | Disulfiram 0.1 uM - DMSO 0.025% | Disulfiram 0.1 uM | DMSO 0.025% | Control | Shuffled | 0.2916667 | 0.6666667 |\n", + "| 3 | Disulfiram 1.0 uM - DMSO 0.025% | Disulfiram 1.0 uM | DMSO 0.025% | Control | Non-shuffled | 0.4313672 | 0.5312500 |\n", + "| 4 | Disulfiram 1.0 uM - DMSO 0.025% | Disulfiram 1.0 uM | DMSO 0.025% | Pyroptosis | Shuffled | 0.3333333 | 0.1458333 |\n", + "| 5 | Disulfiram 2.5 uM - DMSO 0.025% | Disulfiram 2.5 uM | DMSO 0.025% | Control | Non-shuffled | 0.4289863 | 0.5597222 |\n", + "| 6 | DMSO 0.1% - DMSO 1.0% | DMSO 0.1% | DMSO 1.0% | Control | Non-shuffled | 0.9125000 | 0.8916667 |\n", + "\n" + ], + "text/plain": [ + " Metadata_Treatment inducer inhibitor Metadata_labels\n", + "1 Disulfiram 0.1 uM - DMSO 0.025% Disulfiram 0.1 uM DMSO 0.025% Control \n", + "2 Disulfiram 0.1 uM - DMSO 0.025% Disulfiram 0.1 uM DMSO 0.025% Control \n", + "3 Disulfiram 1.0 uM - DMSO 0.025% Disulfiram 1.0 uM DMSO 0.025% Control \n", + "4 Disulfiram 1.0 uM - DMSO 0.025% Disulfiram 1.0 uM DMSO 0.025% Pyroptosis \n", + "5 Disulfiram 2.5 uM - DMSO 0.025% Disulfiram 2.5 uM DMSO 0.025% Control \n", + "6 DMSO 0.1% - DMSO 1.0% DMSO 0.1% DMSO 1.0% Control \n", + " shuffled mAP_moprhology mAP_secretome\n", + "1 Non-shuffled 0.4178662 0.4012085 \n", + "2 Shuffled 0.2916667 0.6666667 \n", + "3 Non-shuffled 0.4313672 0.5312500 \n", + "4 Shuffled 0.3333333 0.1458333 \n", + "5 Non-shuffled 0.4289863 0.5597222 \n", + "6 Non-shuffled 0.9125000 0.8916667 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df <- df %>%\n", + " mutate(Metadata_Treatment = case_when(\n", + " Metadata_Treatment =='DMSO_0.100_%_DMSO_0.025_%' ~ \"DMSO 0.1% - DMSO 0.025%\",\n", + " Metadata_Treatment =='DMSO_0.100_%_DMSO_1.000_%' ~ \"DMSO 0.1% - DMSO 1.0%\",\n", + " Metadata_Treatment =='DMSO_0.100_%_Z-VAD-FMK_100.000_uM' ~ \"DMSO 0.1% - Z-VAD-FMK 100.0 uM\",\n", + " Metadata_Treatment =='DMSO_0.100_%_Z-VAD-FMK_30.000_uM' ~ \"DMSO 0.1% - Z-VAD-FMK 30.0 uM\",\n", + " Metadata_Treatment =='Flagellin_1.000_ug_per_ml_DMSO_0.025_%' ~ \"Flagellin 1.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM' ~ \"Flagellin 1.0 ug/ml - Disulfiram 1.0 uM\",\n", + " Metadata_Treatment =='LPS_0.010_ug_per_ml_DMSO_0.025_%' ~ \"LPS 0.01 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_0.100_ug_per_ml_DMSO_0.025_%' ~ \"LPS 0.1 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Flagellin_0.100_ug_per_ml_DMSO_0.0_%' ~ \"Flagellin 0.1 ug/ml - DMSO 0.0%\",\n", + " Metadata_Treatment =='Flagellin_0.100_ug_per_ml_DMSO_0.025_%' ~ \"Flagellin 0.1 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Disulfiram_0.100_uM_DMSO_0.025_%' ~ \"Disulfiram 0.1 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - Disulfiram 1.0 uM\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - Z-VAD-FMK 100.0 uM\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_1.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Flagellin_1.000_ug_per_ml_DMSO_0.0_%' ~ \"Flagellin 1.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Disulfiram_1.000_uM_DMSO_0.025_%' ~ \"Disulfiram 1.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='Thapsigargin_1.000_uM_DMSO_0.025_%' ~ \"Thapsigargin 1.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='Topotecan_10.000_nM_DMSO_0.025_%' ~ \"Topotecan 10.0 nM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 10.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_0.100_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 0.1 uM\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_1.000_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 1.0 uM\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_2.500_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 2.5 uM\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM' ~ \"LPS 10.0 ug/ml - Z-VAD-FMK 100.0 uM\",\n", + " Metadata_Treatment =='Thapsigargin_10.000_uM_DMSO_0.025_%' ~ \"Thapsigargin 10.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='H2O2_100.000_nM_DMSO_0.025_%' ~ \"H2O2 100.0 nM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_100.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='H2O2_100.000_uM_DMSO_0.025_%' ~ \"H2O2 100.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='H2O2_100.000_uM_Disulfiram_1.000_uM' ~ \"H2O2 100.0 uM - Disulfiram 1.0 uM\",\n", + " Metadata_Treatment =='H2O2_100.000_uM_Z-VAD-FMK_100.000_uM' ~ \"H2O2 100.0 uM - Z-VAD-FMK 100.0 uM\",\n", + " Metadata_Treatment =='Disulfiram_2.500_uM_DMSO_0.025_%' ~ \"Disulfiram 2.5 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='Topotecan_20.000_nM_DMSO_0.025_%' ~ \"Topotecan 20.0 nM - DMSO 0.025%\",\n", + " Metadata_Treatment =='Topotecan_5.000_nM_DMSO_0.025_%' ~ \"Topotecan 5.0 nM - DMSO 0.025%\",\n", + " Metadata_Treatment =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ \"Media ctr 0.0 0\",\n", + " Metadata_Treatment =='media_ctr_0.0_0_Media_0.0_0' ~ \"Media ctr 0.0 0\"\n", + " ))\n", + " # replace Media ctr 0.0 0 with Media\n", + "df$Metadata_Treatment <- gsub(\"Media ctr 0.0 0\", \"Media\", df$Metadata_Treatment)\n", + "\n", + "# split the Metadata_Treatment into two columns by the \" - \" delimiter\n", + "df <- df %>%\n", + " separate(Metadata_Treatment, c(\"inducer\", \"inhibitor\"), sep = \" - \", remove = FALSE)\n", + "\n", + "# replace the inhibitor NA with Media\n", + "df$inhibitor <- ifelse(is.na(df$inhibitor), \"Media\", df$inhibitor)\n", + "\n", + "# make the group_treatment column a factor\n", + "df$inducer <- factor(\n", + " df$inducer,\n", + " levels = c(\n", + " 'Media',\n", + " 'DMSO 0.1%',\n", + "\n", + " 'Flagellin 0.1 ug/ml',\n", + " 'Flagellin 1.0 ug/ml',\n", + "\n", + " 'LPS 0.01 ug/ml',\n", + " 'LPS 0.1 ug/ml',\n", + " 'LPS 1.0 ug/ml',\n", + " 'LPS 10.0 ug/ml',\n", + " 'LPS 100.0 ug/ml',\n", + "\n", + " 'LPS 1.0 ug/ml + Nigericin 1.0 uM',\n", + " 'LPS 1.0 ug/ml + Nigericin 3.0 uM',\n", + " 'LPS 1.0 ug/ml + Nigericin 10.0 uM',\n", + "\n", + " 'LPS 100.0 ug/ml + Nigericin 1.0 uM',\n", + " 'LPS 100.0 ug/ml + Nigericin 3.0 uM',\n", + " 'LPS 100.0 ug/ml + Nigericin 10.0 uM',\n", + "\n", + " 'H2O2 100.0 nM',\n", + " 'H2O2 100.0 uM',\n", + "\n", + " 'Disulfiram 0.1 uM',\n", + " 'Disulfiram 1.0 uM',\n", + " 'Disulfiram 2.5 uM',\n", + "\n", + " 'Thapsigargin 1.0 uM',\n", + " 'Thapsigargin 10.0 uM',\n", + "\n", + " 'Topotecan 5.0 nM',\n", + " 'Topotecan 10.0 nM',\n", + " 'Topotecan 20.0 nM'\n", + " )\n", + ")\n", + "\n", + "# make the group_treatment column a factor\n", + "df$inhibitor <- factor(\n", + " df$inhibitor,\n", + " levels = c(\n", + " 'Media',\n", + " 'DMSO 0.025%',\n", + " 'DMSO 1.0%',\n", + "\n", + " 'Disulfiram 0.1 uM',\n", + " 'Disulfiram 1.0 uM',\n", + " 'Disulfiram 2.5 uM',\n", + "\n", + " 'Z-VAD-FMK 30.0 uM',\n", + " 'Z-VAD-FMK 100.0 uM'\n", + " )\n", + ")\n", + "head(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [], + "source": [ + "# save the df to as parquet for plotting later on\n", + "arrow::write_parquet(df, file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"morphology_secretome_comparison.parquet\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "vscode": { + "languageId": "r" + } + }, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 900, + "width": 900 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "width <- 15\n", + "height <- 15\n", + "options(repr.plot.width=width, repr.plot.height=height)\n", + "# scatter plot with fill being the treatment dose\n", + "scatter_by_treatment <- (\n", + " ggplot(df, aes(x=mAP_moprhology, y=mAP_secretome, col = inducer, shape=inhibitor))\n", + " + geom_point(size=3, alpha=1)\n", + " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", + " + theme_bw()\n", + " + ggtitle(\"Comparison of mAP scores\")\n", + " + ylim(0,1)\n", + " + xlim(0,1)\n", + " + figure_theme\n", + " # Change the legend title\n", + " # change the legend shape\n", + " + scale_color_manual(\n", + " name = \"Inducer\",\n", + " labels = c(\n", + " 'Media',\n", + " 'DMSO 0.1%',\n", + "\n", + " 'Flagellin 0.1 ug/ml',\n", + " 'Flagellin 1.0 ug/ml',\n", + "\n", + " 'LPS 0.01 ug/ml',\n", + " 'LPS 0.1 ug/ml',\n", + " 'LPS 1.0 ug/ml',\n", + " 'LPS 10.0 ug/ml',\n", + " 'LPS 100.0 ug/ml',\n", + "\n", + " 'LPS 1.0 ug/ml + Nigericin 1.0 uM',\n", + " 'LPS 1.0 ug/ml + Nigericin 3.0 uM',\n", + " 'LPS 1.0 ug/ml + Nigericin 10.0 uM',\n", + "\n", + " 'LPS 100.0 ug/ml + Nigericin 1.0 uM',\n", + " 'LPS 100.0 ug/ml + Nigericin 3.0 uM',\n", + " 'LPS 100.0 ug/ml + Nigericin 10.0 uM',\n", + "\n", + " 'H2O2 100.0 nM',\n", + " 'H2O2 100.0 uM',\n", + "\n", + " 'Disulfiram 0.1 uM',\n", + " 'Disulfiram 1.0 uM',\n", + " 'Disulfiram 2.5 uM',\n", + "\n", + " 'Thapsigargin 1.0 uM',\n", + " 'Thapsigargin 10.0 uM',\n", + "\n", + " 'Topotecan 5.0 nM',\n", + " 'Topotecan 10.0 nM',\n", + " 'Topotecan 20.0 nM'\n", + " ),\n", + " values = colors)\n", + " + scale_shape_manual(\n", + " name = \"Inhibitor\",\n", + " labels = c(\n", + " 'Media',\n", + " 'DMSO 0.025%',\n", + " 'DMSO 1.0%',\n", + "\n", + " 'Disulfiram 0.1 uM',\n", + " 'Disulfiram 1.0 uM',\n", + " 'Disulfiram 2.5 uM',\n", + "\n", + " 'Z-VAD-FMK 30.0 uM',\n", + " 'Z-VAD-FMK 100.0 uM'\n", + "\n", + " ),\n", + " values = shapes\n", + " )\n", + " # make the legend 1 column\n", + " + guides(color = guide_legend(ncol = 1), shape = guide_legend(ncol = 1))\n", + " + ggplot2::coord_fixed()\n", + " + facet_grid(shuffled~.)\n", + " # add y = x line\n", + " + geom_abline(intercept = 0, slope = 1, linetype = \"dashed\", color = \"black\")\n", + ")\n", + "scatter_by_treatment" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "R", + "language": "R", + "name": "ir" + }, + "language_info": { + "codemirror_mode": "r", + "file_extension": ".r", + "mimetype": "text/x-r-source", + "name": "R", + "pygments_lexer": "r", + "version": "4.2.2" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/9.mAP/notebooks/3.aggregate_map_scores_secretome.ipynb b/9.mAP/notebooks/3.aggregate_map_scores_secretome.ipynb deleted file mode 100644 index e3f13ce4b..000000000 --- a/9.mAP/notebooks/3.aggregate_map_scores_secretome.ipynb +++ /dev/null @@ -1,454 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pathlib\n", - "import warnings\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "import plotly.express as px\n", - "from copairs.map import aggregate\n", - "\n", - "warnings.filterwarnings(\"ignore\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# Directories\n", - "processed_data_dir = pathlib.Path(\"../data/processed/\")\n", - "sc_ap_scores_dir = (processed_data_dir / \"mAP_scores/secretome\").resolve()\n", - "agg_sc_ap_scores_dir = (processed_data_dir / \"aggregate_mAPs/secretome\").resolve()\n", - "agg_sc_ap_scores_dir.mkdir(parents=True, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Preparing the dataset\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparisonfile
0D06Apoptosis0.8657600.0151527.072.0non-shuffledPyroptosis_vs_Apoptosismerged_sc_agg_ap_scores_class
1B06Control0.9565080.01515275.0140.0non-shuffledPyroptosis_vs_Controlmerged_sc_agg_ap_scores_class
2B02Pyroptosis0.9286840.01515264.0140.0non-shuffledPyroptosis_vs_Controlmerged_sc_agg_ap_scores_class
0B02Pyroptosis0.3876111.00000064.0140.0shuffledPyroptosis_vs_ControlmAP_scores_shuffled_feature_space_class
1B03Pyroptosis0.4555590.74242464.0140.0shuffledPyroptosis_vs_ControlmAP_scores_shuffled_feature_space_class
\n", - "
" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 D06 Apoptosis 0.865760 0.015152 7.0 \n", - "1 B06 Control 0.956508 0.015152 75.0 \n", - "2 B02 Pyroptosis 0.928684 0.015152 64.0 \n", - "0 B02 Pyroptosis 0.387611 1.000000 64.0 \n", - "1 B03 Pyroptosis 0.455559 0.742424 64.0 \n", - "\n", - " n_total_pairs shuffled comparison \\\n", - "0 72.0 non-shuffled Pyroptosis_vs_Apoptosis \n", - "1 140.0 non-shuffled Pyroptosis_vs_Control \n", - "2 140.0 non-shuffled Pyroptosis_vs_Control \n", - "0 140.0 shuffled Pyroptosis_vs_Control \n", - "1 140.0 shuffled Pyroptosis_vs_Control \n", - "\n", - " file \n", - "0 merged_sc_agg_ap_scores_class \n", - "1 merged_sc_agg_ap_scores_class \n", - "2 merged_sc_agg_ap_scores_class \n", - "0 mAP_scores_shuffled_feature_space_class \n", - "1 mAP_scores_shuffled_feature_space_class " - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_files = list(sc_ap_scores_dir.glob(\"*.csv\"))\n", - "# get the files that contain the string class\n", - "class_files = [file for file in all_files if \"class\" in file.stem]\n", - "mAPs = []\n", - "for file in class_files:\n", - " df = pd.read_csv(file)\n", - " df[\"file\"] = file.stem\n", - " mAPs.append(df)\n", - "# single-cell mAP scores\n", - "mAPs = pd.concat(mAPs)\n", - "mAPs.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# grabbing all cp features (regular, feature shuffled and labeled shuffled)\n", - "reg_sc_mAPs = mAPs.loc[mAPs[\"shuffled\"] == \"non-shuffled\"]\n", - "shuffled_feat_sc_mAPs = mAPs.loc[mAPs[\"shuffled\"] == \"features_shuffled\"]\n", - "shuffled_pheno_sc_mAPs = mAPs.loc[mAPs[\"shuffled\"] == \"phenotype_shuffled\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_labelsshuffledsampling_error
0Apoptosisnon-shuffled0.054908
1Apoptosisshuffled0.017341
2Controlnon-shuffled0.006999
3Controlshuffled0.013836
4Pyroptosisnon-shuffled0.006264
\n", - "
" - ], - "text/plain": [ - " Metadata_labels shuffled sampling_error\n", - "0 Apoptosis non-shuffled 0.054908\n", - "1 Apoptosis shuffled 0.017341\n", - "2 Control non-shuffled 0.006999\n", - "3 Control shuffled 0.013836\n", - "4 Pyroptosis non-shuffled 0.006264" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# calculating sampling error\n", - "# grouping dataframe based on phenotype levels, feature and feature types\n", - "df_group = mAPs.groupby(by=[\"Metadata_labels\", \"shuffled\"])\n", - "\n", - "\n", - "sampling_error_df = []\n", - "for name, df in df_group:\n", - " pheno, shuffled_type = name\n", - "\n", - " # caclulating sampling error\n", - " avg_percision = df[\"average_precision\"].values\n", - " sampling_error = np.std(avg_percision) / np.sqrt(len(avg_percision))\n", - "\n", - " sampling_error_df.append([pheno, shuffled_type, sampling_error])\n", - "cols = [\"Metadata_labels\", \"shuffled\", \"sampling_error\"]\n", - "sampling_error_df = pd.DataFrame(sampling_error_df, columns=cols)\n", - "\n", - "\n", - "sampling_error_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_labelsmean_average_precisionnlog10pvalueq_valuenlog10qvalueabove_p_thresholdabove_q_thresholdshuffled
0Apoptosis0.8657601.7914780.0161631.791478TrueTruenon-shuffled
0Apoptosis0.1491420.4645710.3431070.464571FalseFalseshuffled
0Control0.9565081.7189330.0191011.718933TrueTruenon-shuffled
0Control0.7360230.4204000.3798390.420400FalseFalseshuffled
0Pyroptosis0.9286841.8126500.0153941.812650TrueTruenon-shuffled
\n", - "
" - ], - "text/plain": [ - " Metadata_labels mean_average_precision nlog10pvalue q_value \\\n", - "0 Apoptosis 0.865760 1.791478 0.016163 \n", - "0 Apoptosis 0.149142 0.464571 0.343107 \n", - "0 Control 0.956508 1.718933 0.019101 \n", - "0 Control 0.736023 0.420400 0.379839 \n", - "0 Pyroptosis 0.928684 1.812650 0.015394 \n", - "\n", - " nlog10qvalue above_p_threshold above_q_threshold shuffled \n", - "0 1.791478 True True non-shuffled \n", - "0 0.464571 False False shuffled \n", - "0 1.718933 True True non-shuffled \n", - "0 0.420400 False False shuffled \n", - "0 1.812650 True True non-shuffled " - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Generating aggregate scores with a threshold p-value of 0.05\n", - "mAP_dfs = []\n", - "for name, df in tuple(mAPs.groupby(by=[\"Metadata_labels\", \"shuffled\"])):\n", - " agg_df = aggregate(df, sameby=[\"Metadata_labels\"], threshold=0.05)\n", - " agg_df[\"Metadata_labels\"] = name[0]\n", - " agg_df[\"shuffled\"] = name[1]\n", - " mAP_dfs.append(agg_df)\n", - "\n", - "mAP_dfs = pd.concat(mAP_dfs)\n", - "mAP_dfs.to_csv(agg_sc_ap_scores_dir / \"mAP_scores_class.csv\", index=False)\n", - "mAP_dfs.head()" - ] - } - ], - "metadata": { - "interpreter": { - "hash": "2a7bc4b693a428e685bdbc198b90c0fe2d737ece3fda25b7a5d0fc6f41082281" - }, - "kernelspec": { - "display_name": "Python 3.12.0 ('map')", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.2" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.mAP/notebooks/4.generate_map_scores_morphology_treatment.ipynb b/9.mAP/notebooks/4.generate_map_scores_morphology_treatment.ipynb deleted file mode 100644 index 166489e52..000000000 --- a/9.mAP/notebooks/4.generate_map_scores_morphology_treatment.ipynb +++ /dev/null @@ -1,5039 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import itertools\n", - "import logging\n", - "import pathlib\n", - "import sys\n", - "from typing import Optional\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "import toml\n", - "from copairs.map import run_pipeline\n", - "from pycytominer import feature_select\n", - "\n", - "# imports src\n", - "sys.path.append(\"../\")\n", - "from src import utils\n", - "\n", - "# setting up logger\n", - "logging.basicConfig(\n", - " filename=\"map_analysis_testing.log\",\n", - " level=logging.DEBUG,\n", - " format=\"%(levelname)s:%(asctime)s:%(name)s:%(message)s\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Helper functions\n", - "Set of helper functions to help out throughout the notebook" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "## Helper function\n", - "\n", - "\n", - "def shuffle_meta_labels(\n", - " dataset: pd.DataFrame, target_col: str, seed: Optional[int] = 0\n", - ") -> pd.DataFrame:\n", - " \"\"\"shuffles labels or values within a single selected column\n", - "\n", - " Parameters\n", - " ----------\n", - " dataset : pd.DataFrame\n", - " dataframe containing the dataset\n", - "\n", - " target_col : str\n", - " Column to select in order to conduct the shuffling\n", - "\n", - " seed : int\n", - " setting random seed\n", - "\n", - " Returns\n", - " -------\n", - " pd.DataFrame\n", - " shuffled dataset\n", - "\n", - " Raises\n", - " ------\n", - " TypeError\n", - " raised if incorrect types are provided\n", - " \"\"\"\n", - " # setting seed\n", - " np.random.seed(seed)\n", - "\n", - " # type checking\n", - " if not isinstance(target_col, str):\n", - " raise TypeError(\"'target_col' must be a string type\")\n", - " if not isinstance(dataset, pd.DataFrame):\n", - " raise TypeError(\"'dataset' must be a pandas dataframe\")\n", - "\n", - " # selecting column, shuffle values within column, add to dataframe\n", - " # dataset[target_col] = np.random.permutation(dataset[target_col].values)\n", - " for column in dataset.columns:\n", - " if column == target_col:\n", - " np.random.shuffle(dataset[column].values)\n", - " return dataset\n", - "\n", - "\n", - "def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.array:\n", - " \"\"\"suffles all values within feature space\n", - "\n", - " Parameters\n", - " ----------\n", - " feature_vals : np.array\n", - " shuffled\n", - "\n", - " seed : Optional[int]\n", - " setting random seed\n", - "\n", - " Returns\n", - " -------\n", - " np.array\n", - " Returns shuffled values within the feature space\n", - "\n", - " Raises\n", - " ------\n", - " TypeError\n", - " Raised if a numpy array is not provided\n", - " \"\"\"\n", - " # setting seed\n", - " np.random.seed(seed)\n", - "\n", - " # shuffle given array\n", - " if not isinstance(feature_vals, np.ndarray):\n", - " raise TypeError(\"'feature_vals' must be a numpy array\")\n", - " if feature_vals.ndim != 2:\n", - " raise TypeError(\"'feature_vals' must be a 2x2 matrix\")\n", - "\n", - " # creating a copy for feature vales to prevent overwriting of global variables\n", - " feature_vals = np.copy(feature_vals)\n", - "\n", - " # shuffling feature space\n", - " n_cols = feature_vals.shape[1]\n", - " for col_idx in range(0, n_cols):\n", - " # selecting column, shuffle, and update:\n", - " feature_vals[:, col_idx] = np.random.permutation(feature_vals[:, col_idx])\n", - "\n", - " return feature_vals" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setting up Paths and loading data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# load in the treatment groups\n", - "ground_truth = pathlib.Path(\n", - " \"../../4.sc_Morphology_Neural_Network_MLP_Model/MLP_utils/ground_truth.toml\"\n", - ").resolve(strict=True)\n", - "# load in the ground truth\n", - "ground_truth = toml.load(ground_truth)\n", - "apoptosis_ground_truth = ground_truth[\"Apoptosis\"][\"apoptosis_groups_list\"]\n", - "pyroptosis_ground_truth = ground_truth[\"Pyroptosis\"][\"pyroptosis_groups_list\"]\n", - "control_ground_truth = ground_truth[\"Healthy\"][\"healthy_groups_list\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "single_cell_data = pathlib.Path(\n", - " f\"../../data/PBMC_preprocessed_sc_norm_aggregated.parquet\"\n", - ").resolve(strict=True)\n", - "df = pd.read_parquet(single_cell_data)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# out paths\n", - "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/morphology/\")\n", - "map_out_dir.mkdir(exist_ok=True, parents=True)\n", - "\n", - "# regular data output\n", - "# saving to csv\n", - "regular_feat_map_path = pathlib.Path(map_out_dir / \"mAP_scores_regular_treatment.csv\")\n", - "\n", - "# shuffled data output\n", - "shuffled_feat_map_path = pathlib.Path(\n", - " map_out_dir / \"mAP_scores_shuffled_class_treatment.csv\"\n", - ")\n", - "\n", - "# shuffled feature space output\n", - "shuffled_feat_space_map_path = pathlib.Path(\n", - " map_out_dir / \"mAP_scores_shuffled_feature_space_treatment.csv\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Clean up data" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].unique()\n", - "# replace values in the oneb_Metadata_Treatment_Dose_Inhibitor_Dose column\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\n", - " \"Flagellin_0.100_ug_per_ml_DMSO_0.000_%\", \"Flagellin_0.100_ug_per_ml_DMSO_0.025_%\"\n", - ")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\"Flagellin_1.000_0_DMSO_0.025_%\", \"Flagellin_1.000_ug_per_ml_DMSO_0.025_%\")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\n", - " \"Flagellin_1.000_ug_per_ml_DMSO_0.000_%\", \"Flagellin_1.000_ug_per_ml_DMSO_0.025_%\"\n", - ")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\"media_ctr_0.0_0_Media_0_0\", \"Media\")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\"media_ctr_0.0_0_Media_ctr_0.0_0\", \"Media\")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\n", - " \"Flagellin_1.000_0_Disulfiram_1.000_uM\",\n", - " \"Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM\",\n", - ")\n", - "len(df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].unique())\n", - "# add apoptosis, pyroptosis and healthy columns to dataframe\n", - "df[\"Apoptosis\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in apoptosis_ground_truth,\n", - " axis=1,\n", - ")\n", - "df[\"Pyroptosis\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in pyroptosis_ground_truth,\n", - " axis=1,\n", - ")\n", - "df[\"Control\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in control_ground_truth,\n", - " axis=1,\n", - ")\n", - "\n", - "# merge apoptosis, pyroptosis, and healthy columns into one column\n", - "df[\"Metadata_labels\"] = df.apply(\n", - " lambda row: \"Apoptosis\"\n", - " if row[\"Apoptosis\"]\n", - " else \"Pyroptosis\"\n", - " if row[\"Pyroptosis\"]\n", - " else \"Control\",\n", - " axis=1,\n", - ")\n", - "\n", - "# # drop apoptosis, pyroptosis, and healthy columns\n", - "df.drop(columns=[\"Apoptosis\", \"Pyroptosis\", \"Control\"], inplace=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# output directories\n", - "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/\")\n", - "map_out_dir.mkdir(parents=True, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Define the control df" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_Welloneb_Metadata_Treatment_Dose_Inhibitor_DoseCytoplasm_AreaShape_CompactnessCytoplasm_AreaShape_FormFactorCytoplasm_AreaShape_MajorAxisLengthCytoplasm_AreaShape_MinorAxisLengthCytoplasm_AreaShape_OrientationCytoplasm_AreaShape_Zernike_0_0Cytoplasm_AreaShape_Zernike_1_1Cytoplasm_AreaShape_Zernike_2_0...Nuclei_Texture_InverseDifferenceMoment_CorrMito_3_02_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_00_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_01_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_02_256Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_03_256Nuclei_Texture_SumEntropy_CorrPM_3_01_256Nuclei_Texture_SumVariance_CorrPM_3_01_256Nuclei_Texture_Variance_CorrER_3_00_256Nuclei_Texture_Variance_CorrGasdermin_3_00_256Metadata_labels
4B06DMSO_0.100_%_DMSO_0.025_%0.022371-0.022614-0.039573-0.049300-0.013386-0.035579-0.026341-0.034624...0.2794010.0370460.0294860.0301310.033986-0.032881-0.010667-0.027280-0.026652Control
5B07DMSO_0.100_%_DMSO_0.025_%-0.0717530.049418-0.080162-0.1109350.0091020.0187230.0070160.008824...0.2770940.0172330.0047650.0107180.006667-0.009478-0.0062870.0188060.015570Control
15C06DMSO_0.100_%_DMSO_0.025_%0.061913-0.0474120.0522500.0838490.024151-0.026974-0.013448-0.005720...-0.1879340.0722880.0797890.0764120.073141-0.072702-0.0140180.0010920.000683Control
16C07DMSO_0.100_%_DMSO_0.025_%0.028173-0.0288840.0537970.0753520.0093240.0115140.018833-0.006253...-0.2280850.0240260.0307450.0260340.028530-0.034391-0.0080460.0646280.052708Control
81I06DMSO_0.100_%_DMSO_0.025_%0.048882-0.0143560.1103620.115949-0.0054690.0240330.043835-0.037867...-0.128464-0.048425-0.046729-0.039706-0.0386960.0525460.000737-0.009176-0.005408Control
82I07DMSO_0.100_%_DMSO_0.025_%-0.1008670.076349-0.117207-0.154152-0.0114980.024456-0.0140950.037949...-0.284433-0.076275-0.078142-0.072489-0.0790300.0686290.012430-0.035163-0.028315Control
92J06DMSO_0.100_%_DMSO_0.025_%-0.012228-0.005155-0.048954-0.032680-0.012399-0.034741-0.0469500.054012...0.2253800.0562180.0573510.0538010.055496-0.0612070.003581-0.020050-0.017568Control
93J07DMSO_0.100_%_DMSO_0.025_%-0.0001750.0074260.0307080.024561-0.0017920.0182620.021859-0.007972...0.020434-0.083589-0.080232-0.086812-0.0834290.0890280.0218930.0009900.003350Control
\n", - "

8 rows \u00d7 1248 columns

\n", - "
" - ], - "text/plain": [ - " Metadata_Well oneb_Metadata_Treatment_Dose_Inhibitor_Dose \\\n", - "4 B06 DMSO_0.100_%_DMSO_0.025_% \n", - "5 B07 DMSO_0.100_%_DMSO_0.025_% \n", - "15 C06 DMSO_0.100_%_DMSO_0.025_% \n", - "16 C07 DMSO_0.100_%_DMSO_0.025_% \n", - "81 I06 DMSO_0.100_%_DMSO_0.025_% \n", - "82 I07 DMSO_0.100_%_DMSO_0.025_% \n", - "92 J06 DMSO_0.100_%_DMSO_0.025_% \n", - "93 J07 DMSO_0.100_%_DMSO_0.025_% \n", - "\n", - " Cytoplasm_AreaShape_Compactness Cytoplasm_AreaShape_FormFactor \\\n", - "4 0.022371 -0.022614 \n", - "5 -0.071753 0.049418 \n", - "15 0.061913 -0.047412 \n", - "16 0.028173 -0.028884 \n", - "81 0.048882 -0.014356 \n", - "82 -0.100867 0.076349 \n", - "92 -0.012228 -0.005155 \n", - "93 -0.000175 0.007426 \n", - "\n", - " Cytoplasm_AreaShape_MajorAxisLength Cytoplasm_AreaShape_MinorAxisLength \\\n", - "4 -0.039573 -0.049300 \n", - "5 -0.080162 -0.110935 \n", - "15 0.052250 0.083849 \n", - "16 0.053797 0.075352 \n", - "81 0.110362 0.115949 \n", - "82 -0.117207 -0.154152 \n", - "92 -0.048954 -0.032680 \n", - "93 0.030708 0.024561 \n", - "\n", - " Cytoplasm_AreaShape_Orientation Cytoplasm_AreaShape_Zernike_0_0 \\\n", - "4 -0.013386 -0.035579 \n", - "5 0.009102 0.018723 \n", - "15 0.024151 -0.026974 \n", - "16 0.009324 0.011514 \n", - "81 -0.005469 0.024033 \n", - "82 -0.011498 0.024456 \n", - "92 -0.012399 -0.034741 \n", - "93 -0.001792 0.018262 \n", - "\n", - " Cytoplasm_AreaShape_Zernike_1_1 Cytoplasm_AreaShape_Zernike_2_0 ... \\\n", - "4 -0.026341 -0.034624 ... \n", - "5 0.007016 0.008824 ... \n", - "15 -0.013448 -0.005720 ... \n", - "16 0.018833 -0.006253 ... \n", - "81 0.043835 -0.037867 ... \n", - "82 -0.014095 0.037949 ... \n", - "92 -0.046950 0.054012 ... \n", - "93 0.021859 -0.007972 ... \n", - "\n", - " Nuclei_Texture_InverseDifferenceMoment_CorrMito_3_02_256 \\\n", - "4 0.279401 \n", - "5 0.277094 \n", - "15 -0.187934 \n", - "16 -0.228085 \n", - "81 -0.128464 \n", - "82 -0.284433 \n", - "92 0.225380 \n", - "93 0.020434 \n", - "\n", - " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_00_256 \\\n", - "4 0.037046 \n", - "5 0.017233 \n", - "15 0.072288 \n", - "16 0.024026 \n", - "81 -0.048425 \n", - "82 -0.076275 \n", - "92 0.056218 \n", - "93 -0.083589 \n", - "\n", - " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_01_256 \\\n", - "4 0.029486 \n", - "5 0.004765 \n", - "15 0.079789 \n", - "16 0.030745 \n", - "81 -0.046729 \n", - "82 -0.078142 \n", - "92 0.057351 \n", - "93 -0.080232 \n", - "\n", - " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_02_256 \\\n", - "4 0.030131 \n", - "5 0.010718 \n", - "15 0.076412 \n", - "16 0.026034 \n", - "81 -0.039706 \n", - "82 -0.072489 \n", - "92 0.053801 \n", - "93 -0.086812 \n", - "\n", - " Nuclei_Texture_InverseDifferenceMoment_CorrPM_3_03_256 \\\n", - "4 0.033986 \n", - "5 0.006667 \n", - "15 0.073141 \n", - "16 0.028530 \n", - "81 -0.038696 \n", - "82 -0.079030 \n", - "92 0.055496 \n", - "93 -0.083429 \n", - "\n", - " Nuclei_Texture_SumEntropy_CorrPM_3_01_256 \\\n", - "4 -0.032881 \n", - "5 -0.009478 \n", - "15 -0.072702 \n", - "16 -0.034391 \n", - "81 0.052546 \n", - "82 0.068629 \n", - "92 -0.061207 \n", - "93 0.089028 \n", - "\n", - " Nuclei_Texture_SumVariance_CorrPM_3_01_256 \\\n", - "4 -0.010667 \n", - "5 -0.006287 \n", - "15 -0.014018 \n", - "16 -0.008046 \n", - "81 0.000737 \n", - "82 0.012430 \n", - "92 0.003581 \n", - "93 0.021893 \n", - "\n", - " Nuclei_Texture_Variance_CorrER_3_00_256 \\\n", - "4 -0.027280 \n", - "5 0.018806 \n", - "15 0.001092 \n", - "16 0.064628 \n", - "81 -0.009176 \n", - "82 -0.035163 \n", - "92 -0.020050 \n", - "93 0.000990 \n", - "\n", - " Nuclei_Texture_Variance_CorrGasdermin_3_00_256 Metadata_labels \n", - "4 -0.026652 Control \n", - "5 0.015570 Control \n", - "15 0.000683 Control \n", - "16 0.052708 Control \n", - "81 -0.005408 Control \n", - "82 -0.028315 Control \n", - "92 -0.017568 Control \n", - "93 0.003350 Control \n", - "\n", - "[8 rows x 1248 columns]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "control_df = df[\n", - " df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] == \"DMSO_0.100_%_DMSO_0.025_%\"\n", - "]\n", - "control_df" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP Pipeline Parameters" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The null size needs to be determined for the mAP pipeline. This is the size of the null class that is used to determine the mAP score." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "4\n" - ] - } - ], - "source": [ - "tmp = (\n", - " df.groupby([\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"])\n", - " .count()\n", - " .reset_index()[[\"Metadata_Well\", \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]]\n", - ")\n", - "# get the counts of each oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "min_count = tmp[\"Metadata_Well\"].min()\n", - "print(min_count)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Positive pairs: profiles in the same group\n", - "Negative pairs: profiles in different groups\n", - "\n", - "\n", - "pos_sameby = Treatment group: All profiles that have the same treatment group\n", - "pos_diffby = Treatment replicates: In this case - wells\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "pos_sameby = [\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - "pos_diffby = [\"Metadata_Well\"]\n", - "\n", - "neg_sameby = []\n", - "neg_diffby = [\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - "\n", - "# null_size = min_count\n", - "null_size = 100000\n", - "batch_size = 1" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP analysis for non-shuffled data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Loop through the data and determine the mAP score for each treatment in a class compared to a whole other class\n", - "Ex. Pyroptosis treatment 1 (LPS 1.0 ug/mL) vs. All Apoptosis treatments \n", - "Ex. Pyroptosis treatment 1 (LPS 1.0 ug/mL) vs. All Control treatments" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "results_df = pd.DataFrame(\n", - " columns=[\n", - " \"Metadata_Well\",\n", - " \"Metadata_labels\",\n", - " \"average_precision\",\n", - " \"p_value\",\n", - " \"n_pos_pairs\",\n", - " \"n_total_pairs\",\n", - " \"shuffled\",\n", - " \"comparison\",\n", - " ]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "# remove the control group from the dataframe\n", - "df = df[\n", - " df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] != \"DMSO_0.100_%_DMSO_0.025_%\"\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['LPS_0.010_ug_per_ml_DMSO_0.025_%' 'DMSO_0.100_%_DMSO_0.025_%']\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "b529e63bba234bbdb52f246542d8a9c4", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/34 [00:00\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_Welloneb_Metadata_Treatment_Dose_Inhibitor_DoseMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparison
0O02LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...Control1.0000000.0062303.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
1O03LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...Control1.0000000.0062303.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
2O08LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...Control1.0000000.0062303.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
3O09LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...Control1.0000000.0062303.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
4B06DMSO_0.100_%_DMSO_0.025_%Control0.6743560.5934747.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
5B07DMSO_0.100_%_DMSO_0.025_%Control0.5886420.8300827.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
6C06DMSO_0.100_%_DMSO_0.025_%Control0.7202740.4504357.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
7C07DMSO_0.100_%_DMSO_0.025_%Control0.8373380.1628487.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
8I06DMSO_0.100_%_DMSO_0.025_%Control0.7661930.3263777.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
9I07DMSO_0.100_%_DMSO_0.025_%Control0.5988460.8116527.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
10J06DMSO_0.100_%_DMSO_0.025_%Control0.6512270.6622237.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
11J07DMSO_0.100_%_DMSO_0.025_%Control0.8468610.1411497.011.0non-shuffledLPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
\n", - "" - ], - "text/plain": [ - " Metadata_Well oneb_Metadata_Treatment_Dose_Inhibitor_Dose \\\n", - "0 O02 LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "1 O03 LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "2 O08 LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "3 O09 LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "4 B06 DMSO_0.100_%_DMSO_0.025_% \n", - "5 B07 DMSO_0.100_%_DMSO_0.025_% \n", - "6 C06 DMSO_0.100_%_DMSO_0.025_% \n", - "7 C07 DMSO_0.100_%_DMSO_0.025_% \n", - "8 I06 DMSO_0.100_%_DMSO_0.025_% \n", - "9 I07 DMSO_0.100_%_DMSO_0.025_% \n", - "10 J06 DMSO_0.100_%_DMSO_0.025_% \n", - "11 J07 DMSO_0.100_%_DMSO_0.025_% \n", - "\n", - " Metadata_labels average_precision p_value n_pos_pairs n_total_pairs \\\n", - "0 Control 1.000000 0.006230 3.0 11.0 \n", - "1 Control 1.000000 0.006230 3.0 11.0 \n", - "2 Control 1.000000 0.006230 3.0 11.0 \n", - "3 Control 1.000000 0.006230 3.0 11.0 \n", - "4 Control 0.674356 0.593474 7.0 11.0 \n", - "5 Control 0.588642 0.830082 7.0 11.0 \n", - "6 Control 0.720274 0.450435 7.0 11.0 \n", - "7 Control 0.837338 0.162848 7.0 11.0 \n", - "8 Control 0.766193 0.326377 7.0 11.0 \n", - "9 Control 0.598846 0.811652 7.0 11.0 \n", - "10 Control 0.651227 0.662223 7.0 11.0 \n", - "11 Control 0.846861 0.141149 7.0 11.0 \n", - "\n", - " shuffled comparison \n", - "0 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "1 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "2 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "3 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "4 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "5 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "6 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "7 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "8 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "9 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "10 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... \n", - "11 non-shuffled LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-... " - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "# plot the average precision scores on a number line\n", - "import seaborn as sns\n", - "\n", - "# plot the average precision scores\n", - "sns.set(style=\"whitegrid\")\n", - "plt.figure(figsize=(10, 5))\n", - "ax = sns.barplot(\n", - " x=\"comparison\", y=\"average_precision\", hue=\"Metadata_Well\", data=result\n", - ")\n", - "plt.title(\"Average Precision Scores\")\n", - "# legend on the right\n", - "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparisononeb_Metadata_Treatment_Dose_Inhibitor_Dose
0B02Pyroptosis1.0000000.0062303.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%LPS_0.010_ug_per_ml_DMSO_0.025_%
1B03Pyroptosis0.5888890.1704583.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%LPS_0.010_ug_per_ml_DMSO_0.025_%
2B08Pyroptosis1.0000000.0062303.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%LPS_0.010_ug_per_ml_DMSO_0.025_%
3B09Pyroptosis1.0000000.0062303.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%LPS_0.010_ug_per_ml_DMSO_0.025_%
4B06Control0.6743560.5934747.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
5B07Control0.5076890.9704807.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
6C06Control0.7667590.3231677.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
7C07Control0.8596170.1203297.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
8I06Control0.7856370.2778877.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
9I07Control0.5036080.9793407.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
10J06Control0.6750360.5872547.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
11J07Control0.7142080.4815857.011.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
0B04Pyroptosis0.9166670.0128203.011.0non-shuffledLPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...
1B05Pyroptosis1.0000000.0062303.011.0non-shuffledLPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...
2B10Pyroptosis1.0000000.0062303.011.0non-shuffledLPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...
\n", - "
" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 B02 Pyroptosis 1.000000 0.006230 3.0 \n", - "1 B03 Pyroptosis 0.588889 0.170458 3.0 \n", - "2 B08 Pyroptosis 1.000000 0.006230 3.0 \n", - "3 B09 Pyroptosis 1.000000 0.006230 3.0 \n", - "4 B06 Control 0.674356 0.593474 7.0 \n", - "5 B07 Control 0.507689 0.970480 7.0 \n", - "6 C06 Control 0.766759 0.323167 7.0 \n", - "7 C07 Control 0.859617 0.120329 7.0 \n", - "8 I06 Control 0.785637 0.277887 7.0 \n", - "9 I07 Control 0.503608 0.979340 7.0 \n", - "10 J06 Control 0.675036 0.587254 7.0 \n", - "11 J07 Control 0.714208 0.481585 7.0 \n", - "0 B04 Pyroptosis 0.916667 0.012820 3.0 \n", - "1 B05 Pyroptosis 1.000000 0.006230 3.0 \n", - "2 B10 Pyroptosis 1.000000 0.006230 3.0 \n", - "\n", - " n_total_pairs shuffled \\\n", - "0 11.0 non-shuffled \n", - "1 11.0 non-shuffled \n", - "2 11.0 non-shuffled \n", - "3 11.0 non-shuffled \n", - "4 11.0 non-shuffled \n", - "5 11.0 non-shuffled \n", - "6 11.0 non-shuffled \n", - "7 11.0 non-shuffled \n", - "8 11.0 non-shuffled \n", - "9 11.0 non-shuffled \n", - "10 11.0 non-shuffled \n", - "11 11.0 non-shuffled \n", - "0 11.0 non-shuffled \n", - "1 11.0 non-shuffled \n", - "2 11.0 non-shuffled \n", - "\n", - " comparison \\\n", - "0 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "1 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "2 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "3 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "4 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "5 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "6 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "7 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "8 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "9 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "10 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "11 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "0 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", - "1 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", - "2 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", - "\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose \n", - "0 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "1 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "2 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "3 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "4 DMSO_0.100_%_DMSO_0.025_% \n", - "5 DMSO_0.100_%_DMSO_0.025_% \n", - "6 DMSO_0.100_%_DMSO_0.025_% \n", - "7 DMSO_0.100_%_DMSO_0.025_% \n", - "8 DMSO_0.100_%_DMSO_0.025_% \n", - "9 DMSO_0.100_%_DMSO_0.025_% \n", - "10 DMSO_0.100_%_DMSO_0.025_% \n", - "11 DMSO_0.100_%_DMSO_0.025_% \n", - "0 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", - "1 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... \n", - "2 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_... " - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "results_df.head(15)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP analysis for shuffled data (Feature space)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "results_df = pd.DataFrame(\n", - " columns=[\n", - " \"Metadata_Well\",\n", - " \"Metadata_labels\",\n", - " \"average_precision\",\n", - " \"p_value\",\n", - " \"n_pos_pairs\",\n", - " \"n_total_pairs\",\n", - " \"shuffled\",\n", - " \"comparison\",\n", - " ]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2c2a3e6ddde74b2a80e11709b921332a", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/34 [00:00\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparisononeb_Metadata_Treatment_Dose_Inhibitor_Dose
0B02Pyroptosis0.3242420.6178543.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%LPS_0.010_ug_per_ml_DMSO_0.025_%
1B03Pyroptosis0.8333330.0190003.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%LPS_0.010_ug_per_ml_DMSO_0.025_%
2B08Pyroptosis0.4444440.3684463.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%LPS_0.010_ug_per_ml_DMSO_0.025_%
3B09Pyroptosis0.3316500.6054843.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%LPS_0.010_ug_per_ml_DMSO_0.025_%
4B06Control0.8373380.1628487.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
5B07Control0.9276440.0295507.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
6C06Control0.7250000.4416567.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
7C07Control0.5655120.8820417.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
8I06Control0.7631310.3386877.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
9I07Control0.5804420.8453027.011.0shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%DMSO_0.100_%_DMSO_0.025_%
\n", - "" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 B02 Pyroptosis 0.324242 0.617854 3.0 \n", - "1 B03 Pyroptosis 0.833333 0.019000 3.0 \n", - "2 B08 Pyroptosis 0.444444 0.368446 3.0 \n", - "3 B09 Pyroptosis 0.331650 0.605484 3.0 \n", - "4 B06 Control 0.837338 0.162848 7.0 \n", - "5 B07 Control 0.927644 0.029550 7.0 \n", - "6 C06 Control 0.725000 0.441656 7.0 \n", - "7 C07 Control 0.565512 0.882041 7.0 \n", - "8 I06 Control 0.763131 0.338687 7.0 \n", - "9 I07 Control 0.580442 0.845302 7.0 \n", - "\n", - " n_total_pairs shuffled comparison \\\n", - "0 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "1 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "2 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "3 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "4 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "5 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "6 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "7 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "8 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "9 11.0 shuffled LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose \n", - "0 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "1 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "2 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "3 LPS_0.010_ug_per_ml_DMSO_0.025_% \n", - "4 DMSO_0.100_%_DMSO_0.025_% \n", - "5 DMSO_0.100_%_DMSO_0.025_% \n", - "6 DMSO_0.100_%_DMSO_0.025_% \n", - "7 DMSO_0.100_%_DMSO_0.025_% \n", - "8 DMSO_0.100_%_DMSO_0.025_% \n", - "9 DMSO_0.100_%_DMSO_0.025_% " - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "for i in df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].unique():\n", - " # manually get treatment\n", - " tmp = df[\n", - " df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].str.contains(i)\n", - " ].reset_index(drop=True)\n", - "\n", - " # concat tmp and concrol_df\n", - " tmp1 = pd.concat([tmp, control_df]).reset_index(drop=True)\n", - "\n", - " # spliting metadata and raw feature values\n", - " logging.info(\"splitting data set into metadata and raw feature values\")\n", - " df_meta, df_feats = utils.split_data(tmp1)\n", - " df_feats = np.array(df_feats)\n", - " seed = np.random.randint(0, 100)\n", - "\n", - " # shuffling the features, this will overwrite the generated feature space from above with the shuffled one\n", - " df_feats = shuffle_features(feature_vals=df_feats, seed=seed)\n", - "\n", - " try:\n", - " # execute pipeline on negative control with trianing dataset with cp features\n", - "\n", - " logging.info(f\"Running pipeline on CP features using phenotype\")\n", - " result = run_pipeline(\n", - " meta=df_meta,\n", - " feats=df_feats,\n", - " pos_sameby=pos_sameby,\n", - " pos_diffby=pos_diffby,\n", - " neg_sameby=neg_sameby,\n", - " neg_diffby=neg_diffby,\n", - " batch_size=batch_size,\n", - " null_size=null_size,\n", - " )\n", - "\n", - " result[\"shuffled\"] = \"shuffled\"\n", - " result[\"comparison\"] = i\n", - "\n", - " except ZeroDivisionError as e:\n", - " logging.warning(f\"{e} captured on phenotye:. Skipping\")\n", - "\n", - " # concatenating all datasets\n", - " results_df = pd.concat([results_df, result], ignore_index=True)\n", - "# saving to csv\n", - "results_df.to_csv(shuffled_feat_space_map_path, index=False)\n", - "results_df.head(10)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "map", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.mAP/notebooks/5.aggregate_map_scores_morphology_treatment.ipynb b/9.mAP/notebooks/5.aggregate_map_scores_morphology_treatment.ipynb deleted file mode 100644 index eb74abe64..000000000 --- a/9.mAP/notebooks/5.aggregate_map_scores_morphology_treatment.ipynb +++ /dev/null @@ -1,475 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pathlib\n", - "import warnings\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "import plotly.express as px\n", - "from copairs.map import aggregate\n", - "\n", - "warnings.filterwarnings(\"ignore\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# Directories\n", - "processed_data_dir = pathlib.Path(\"../data/processed/\")\n", - "sc_ap_scores_dir = (processed_data_dir / \"mAP_scores/morphology\").resolve()\n", - "agg_sc_ap_scores_dir = (processed_data_dir / \"aggregate_mAPs/morphology\").resolve()\n", - "agg_sc_ap_scores_dir.mkdir(parents=True, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Preparing the dataset\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparisononeb_Metadata_Treatment_Dose_Inhibitor_Dosefile
0B02Pyroptosis1.0000001.03.03.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs...LPS_0.010_ug_per_ml_DMSO_0.025_%mAP_scores_regular_treatment
1B03Pyroptosis1.0000001.03.03.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs...LPS_0.010_ug_per_ml_DMSO_0.025_%mAP_scores_regular_treatment
2B08Pyroptosis1.0000001.03.03.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs...LPS_0.010_ug_per_ml_DMSO_0.025_%mAP_scores_regular_treatment
3B09Pyroptosis1.0000001.03.03.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs...LPS_0.010_ug_per_ml_DMSO_0.025_%mAP_scores_regular_treatment
4B06Control0.0719881.07.077.0non-shuffledLPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs...DMSO_0.100_%_DMSO_0.025_%mAP_scores_regular_treatment
\n", - "
" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 B02 Pyroptosis 1.000000 1.0 3.0 \n", - "1 B03 Pyroptosis 1.000000 1.0 3.0 \n", - "2 B08 Pyroptosis 1.000000 1.0 3.0 \n", - "3 B09 Pyroptosis 1.000000 1.0 3.0 \n", - "4 B06 Control 0.071988 1.0 7.0 \n", - "\n", - " n_total_pairs shuffled \\\n", - "0 3.0 non-shuffled \n", - "1 3.0 non-shuffled \n", - "2 3.0 non-shuffled \n", - "3 3.0 non-shuffled \n", - "4 77.0 non-shuffled \n", - "\n", - " comparison \\\n", - "0 LPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs... \n", - "1 LPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs... \n", - "2 LPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs... \n", - "3 LPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs... \n", - "4 LPS_0.010_ug_per_ml_DMSO_0.025_%_Pyroptosis_vs... \n", - "\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose file \n", - "0 LPS_0.010_ug_per_ml_DMSO_0.025_% mAP_scores_regular_treatment \n", - "1 LPS_0.010_ug_per_ml_DMSO_0.025_% mAP_scores_regular_treatment \n", - "2 LPS_0.010_ug_per_ml_DMSO_0.025_% mAP_scores_regular_treatment \n", - "3 LPS_0.010_ug_per_ml_DMSO_0.025_% mAP_scores_regular_treatment \n", - "4 DMSO_0.100_%_DMSO_0.025_% mAP_scores_regular_treatment " - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_files = list(sc_ap_scores_dir.glob(\"*.csv\"))\n", - "# get the files that contain the string class\n", - "class_files = [file for file in all_files if \"treatment\" in file.stem]\n", - "mAPs = []\n", - "for file in class_files:\n", - " df = pd.read_csv(file)\n", - " df[\"file\"] = file.stem\n", - " mAPs.append(df)\n", - "# single-cell mAP scores\n", - "mAPs = pd.concat(mAPs)\n", - "mAPs.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# grabbing all cp features (regular, feature shuffled and labeled shuffled)\n", - "reg_sc_mAPs = mAPs.loc[mAPs[\"shuffled\"] == \"non-shuffled\"]\n", - "shuffled_feat_sc_mAPs = mAPs.loc[mAPs[\"shuffled\"] == \"features_shuffled\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
oneb_Metadata_Treatment_Dose_Inhibitor_Doseshuffledsampling_error
0DMSO_0.100_%_DMSO_0.025_%non-shuffled0.007061
1DMSO_0.100_%_DMSO_1.000_%non-shuffled0.016898
2DMSO_0.100_%_Z-VAD-FMK_100.000_uMnon-shuffled0.010757
3DMSO_0.100_%_Z-VAD-FMK_30.000_uMnon-shuffled0.015292
4Disulfiram_0.100_uM_DMSO_0.025_%non-shuffled0.010588
\n", - "
" - ], - "text/plain": [ - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose shuffled sampling_error\n", - "0 DMSO_0.100_%_DMSO_0.025_% non-shuffled 0.007061\n", - "1 DMSO_0.100_%_DMSO_1.000_% non-shuffled 0.016898\n", - "2 DMSO_0.100_%_Z-VAD-FMK_100.000_uM non-shuffled 0.010757\n", - "3 DMSO_0.100_%_Z-VAD-FMK_30.000_uM non-shuffled 0.015292\n", - "4 Disulfiram_0.100_uM_DMSO_0.025_% non-shuffled 0.010588" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# grouping dataframe based on phenotype levels, feature and feature types\n", - "df_group = mAPs.groupby(by=[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\", \"shuffled\"])\n", - "\n", - "# calculating sampling error\n", - "sampling_error_df = []\n", - "for name, df in df_group:\n", - " pheno, shuffled_type = name\n", - "\n", - " # caclulating sampling error\n", - " avg_percision = df[\"average_precision\"].values\n", - " sampling_error = np.std(avg_percision) / np.sqrt(len(avg_percision))\n", - "\n", - " sampling_error_df.append([pheno, shuffled_type, sampling_error])\n", - "cols = [\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\", \"shuffled\", \"sampling_error\"]\n", - "sampling_error_df = pd.DataFrame(sampling_error_df, columns=cols)\n", - "\n", - "sampling_error_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
oneb_Metadata_Treatment_Dose_Inhibitor_Dosemean_average_precisionnlog10pvalueq_valuenlog10qvalueabove_p_thresholdabove_q_thresholdshuffled
0DMSO_0.100_%_DMSO_0.025_%0.175935-0.000001.0-0.00000FalseFalsenon-shuffled
0DMSO_0.100_%_DMSO_1.000_%0.5832960.698970.20.69897FalseFalsenon-shuffled
0DMSO_0.100_%_Z-VAD-FMK_100.000_uM0.4011860.698970.20.69897FalseFalsenon-shuffled
0DMSO_0.100_%_Z-VAD-FMK_30.000_uM0.4079080.698970.20.69897FalseFalsenon-shuffled
0Disulfiram_0.100_uM_DMSO_0.025_%0.1104720.096910.80.09691FalseFalsenon-shuffled
\n", - "
" - ], - "text/plain": [ - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose mean_average_precision \\\n", - "0 DMSO_0.100_%_DMSO_0.025_% 0.175935 \n", - "0 DMSO_0.100_%_DMSO_1.000_% 0.583296 \n", - "0 DMSO_0.100_%_Z-VAD-FMK_100.000_uM 0.401186 \n", - "0 DMSO_0.100_%_Z-VAD-FMK_30.000_uM 0.407908 \n", - "0 Disulfiram_0.100_uM_DMSO_0.025_% 0.110472 \n", - "\n", - " nlog10pvalue q_value nlog10qvalue above_p_threshold above_q_threshold \\\n", - "0 -0.00000 1.0 -0.00000 False False \n", - "0 0.69897 0.2 0.69897 False False \n", - "0 0.69897 0.2 0.69897 False False \n", - "0 0.69897 0.2 0.69897 False False \n", - "0 0.09691 0.8 0.09691 False False \n", - "\n", - " shuffled \n", - "0 non-shuffled \n", - "0 non-shuffled \n", - "0 non-shuffled \n", - "0 non-shuffled \n", - "0 non-shuffled " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Generating aggregate scores with a threshold p-value of 0.05\n", - "mAP_dfs = []\n", - "for name, df in tuple(\n", - " mAPs.groupby(by=[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\", \"shuffled\"])\n", - "):\n", - " agg_df = aggregate(\n", - " df, sameby=[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"], threshold=0.05\n", - " )\n", - " agg_df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = name[0]\n", - " agg_df[\"shuffled\"] = name[1]\n", - " mAP_dfs.append(agg_df)\n", - "\n", - "mAP_dfs = pd.concat(mAP_dfs)\n", - "mAP_dfs.to_csv(agg_sc_ap_scores_dir / \"mAP_scores_treatment.csv\", index=False)\n", - "mAP_dfs.head()" - ] - } - ], - "metadata": { - "interpreter": { - "hash": "2a7bc4b693a428e685bdbc198b90c0fe2d737ece3fda25b7a5d0fc6f41082281" - }, - "kernelspec": { - "display_name": "Python 3.12.0 ('map')", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.mAP/notebooks/6.generate_map_scores_secretome_treatment.ipynb b/9.mAP/notebooks/6.generate_map_scores_secretome_treatment.ipynb deleted file mode 100644 index 8ca9a4258..000000000 --- a/9.mAP/notebooks/6.generate_map_scores_secretome_treatment.ipynb +++ /dev/null @@ -1,5813 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import itertools\n", - "import logging\n", - "import pathlib\n", - "import sys\n", - "from typing import Optional\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "import toml\n", - "from copairs.map import run_pipeline\n", - "from pycytominer import feature_select\n", - "\n", - "# imports src\n", - "sys.path.append(\"../\")\n", - "from src import utils\n", - "\n", - "# setting up logger\n", - "logging.basicConfig(\n", - " filename=\"map_analysis_testing.log\",\n", - " level=logging.DEBUG,\n", - " format=\"%(levelname)s:%(asctime)s:%(name)s:%(message)s\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Helper functions\n", - "Set of helper functions to help out throughout the notebook" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "## Helper function\n", - "\n", - "\n", - "def shuffle_meta_labels(\n", - " dataset: pd.DataFrame, target_col: str, seed: Optional[int] = 0\n", - ") -> pd.DataFrame:\n", - " \"\"\"shuffles labels or values within a single selected column\n", - "\n", - " Parameters\n", - " ----------\n", - " dataset : pd.DataFrame\n", - " dataframe containing the dataset\n", - "\n", - " target_col : str\n", - " Column to select in order to conduct the shuffling\n", - "\n", - " seed : int\n", - " setting random seed\n", - "\n", - " Returns\n", - " -------\n", - " pd.DataFrame\n", - " shuffled dataset\n", - "\n", - " Raises\n", - " ------\n", - " TypeError\n", - " raised if incorrect types are provided\n", - " \"\"\"\n", - " # setting seed\n", - " np.random.seed(seed)\n", - "\n", - " # type checking\n", - " if not isinstance(target_col, str):\n", - " raise TypeError(\"'target_col' must be a string type\")\n", - " if not isinstance(dataset, pd.DataFrame):\n", - " raise TypeError(\"'dataset' must be a pandas dataframe\")\n", - "\n", - " # selecting column, shuffle values within column, add to dataframe\n", - " dataset[target_col] = np.random.permutation(dataset[target_col].values)\n", - " return dataset\n", - "\n", - "\n", - "def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.array:\n", - " \"\"\"suffles all values within feature space\n", - "\n", - " Parameters\n", - " ----------\n", - " feature_vals : np.array\n", - " shuffled\n", - "\n", - " seed : Optional[int]\n", - " setting random seed\n", - "\n", - " Returns\n", - " -------\n", - " np.array\n", - " Returns shuffled values within the feature space\n", - "\n", - " Raises\n", - " ------\n", - " TypeError\n", - " Raised if a numpy array is not provided\n", - " \"\"\"\n", - " # setting seed\n", - " np.random.seed(seed)\n", - "\n", - " # shuffle given array\n", - " if not isinstance(feature_vals, np.ndarray):\n", - " raise TypeError(\"'feature_vals' must be a numpy array\")\n", - " if feature_vals.ndim != 2:\n", - " raise TypeError(\"'feature_vals' must be a 2x2 matrix\")\n", - "\n", - " # creating a copy for feature vales to prevent overwriting of global variables\n", - " feature_vals = np.copy(feature_vals)\n", - "\n", - " # shuffling feature space\n", - " n_cols = feature_vals.shape[1]\n", - " for col_idx in range(0, n_cols):\n", - " # selecting column, shuffle, and update:\n", - " feature_vals[:, col_idx] = np.random.permutation(feature_vals[:, col_idx])\n", - "\n", - " return feature_vals" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setting up Paths and loading data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# load in the treatment groups\n", - "ground_truth = pathlib.Path(\n", - " \"../../4.sc_Morphology_Neural_Network_MLP_Model/MLP_utils/ground_truth.toml\"\n", - ").resolve(strict=True)\n", - "# load in the ground truth\n", - "ground_truth = toml.load(ground_truth)\n", - "apoptosis_ground_truth = ground_truth[\"Apoptosis\"][\"apoptosis_groups_list\"]\n", - "pyroptosis_ground_truth = ground_truth[\"Pyroptosis\"][\"pyroptosis_groups_list\"]\n", - "control_ground_truth = ground_truth[\"Healthy\"][\"healthy_groups_list\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "single_cell_data = pathlib.Path(\n", - " f\"../../2.Nomic_nELISA_Analysis/Data/clean/Plate2/nELISA_plate_430420_PBMC_clean.parquet\"\n", - ").resolve(strict=True)\n", - "df = pd.read_parquet(single_cell_data)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
plate_nameplate_barcodeposition_xcell_typeincubation inducerinhibitorinhibitor_concentration_valueinhibitor_concentration_unitinhibitor_concentrationinducer1...VEGF-D [NSU]VEGFR-1 [NSU]WISP-1 (CCN4) [NSU]XCL1 (Lymphotactin) [NSU]TreatmentDoseoneb_Treatment_Dose_Inhibitor_Dosetwob_Treatment_Dose_Inhibitor_Dosethreeb_Treatment_Dose_Inhibitor_Dosefourb_Treatment_Dose_Inhibitor_Dose
070117_20230210MM1_P1430420B06PBMC6_hDMSO0.025%0.030DMSO...0.2588340.2383580.5242760.250670DMSO0.100_%DMSO_0.100_%_DMSO_0.025_%DMSO_DMSO_0.100_%DMSO__0.100_%__DMSO_0.030DMSO__0.100_%__DMSO__0.030
170117_20230210MM1_P1430420C06PBMC6_hDMSO0.025%0.030DMSO...0.3811700.1686450.4550920.228752DMSO0.100_%DMSO_0.100_%_DMSO_0.025_%DMSO_DMSO_0.100_%DMSO__0.100_%__DMSO_0.030DMSO__0.100_%__DMSO__0.030
270117_20230210MM1_P1430420I06PBMC6_hDMSO0.025%0.030DMSO...0.1829560.2632810.2135960.064645DMSO0.100_%DMSO_0.100_%_DMSO_0.025_%DMSO_DMSO_0.100_%DMSO__0.100_%__DMSO_0.030DMSO__0.100_%__DMSO__0.030
370117_20230210MM1_P1430420J06PBMC6_hDMSO0.025%0.030DMSO...0.5820530.0875650.1409920.234191DMSO0.100_%DMSO_0.100_%_DMSO_0.025_%DMSO_DMSO_0.100_%DMSO__0.100_%__DMSO_0.030DMSO__0.100_%__DMSO__0.030
470117_20230210MM1_P1430420B07PBMC6_hDMSO0.025%0.030DMSO...0.2641410.2967820.5416890.167078DMSO0.100_%DMSO_0.100_%_DMSO_0.025_%DMSO_DMSO_0.100_%DMSO__0.100_%__DMSO_0.030DMSO__0.100_%__DMSO__0.030
..................................................................
14970117_20230210MM1_P1430420O05PBMC6_hMedia_ctrNaNnan0.0media_ctr...0.2759410.3125660.2860310.288358media_ctr0.0_nanmedia_ctr_0.0_0_Media_ctr_0.0_0media_ctr_Media_ctr_0.0_nanmedia_ctr__0.0_nan__Media_ctr_0.0media_ctr__0.0_nan__Media_ctr__0.0
15070117_20230210MM1_P1430420O10PBMC6_hMedia_ctrNaNnan0.0media_ctr...0.4507150.1780110.6211190.229238media_ctr0.0_nanmedia_ctr_0.0_0_Media_ctr_0.0_0media_ctr_Media_ctr_0.0_nanmedia_ctr__0.0_nan__Media_ctr_0.0media_ctr__0.0_nan__Media_ctr__0.0
15170117_20230210MM1_P1430420O11PBMC6_hMediaNaNnan0.0media_ctr...0.3089650.2687300.6130260.254080media_ctr0.0_nanmedia_ctr_0.0_0_Media_0.0_0media_ctr_Media_0.0_nanmedia_ctr__0.0_nan__Media_0.0media_ctr__0.0_nan__Media__0.0
15270117_20230210MM1_P1430420B12PBMC6_hMedia_ctrNaNnan0.0media_ctr...0.1613220.2969840.6259910.297158media_ctr0.0_nanmedia_ctr_0.0_0_Media_ctr_0.0_0media_ctr_Media_ctr_0.0_nanmedia_ctr__0.0_nan__Media_ctr_0.0media_ctr__0.0_nan__Media_ctr__0.0
15370117_20230210MM1_P1430420I12PBMC6_hMedia_ctrNaNnan0.0media_ctr...0.3674500.2486190.4049640.290474media_ctr0.0_nanmedia_ctr_0.0_0_Media_ctr_0.0_0media_ctr_Media_ctr_0.0_nanmedia_ctr__0.0_nan__Media_ctr_0.0media_ctr__0.0_nan__Media_ctr__0.0
\n", - "

154 rows \u00d7 218 columns

\n", - "
" - ], - "text/plain": [ - " plate_name plate_barcode position_x cell_type \\\n", - "0 70117_20230210MM1_P1 430420 B06 PBMC \n", - "1 70117_20230210MM1_P1 430420 C06 PBMC \n", - "2 70117_20230210MM1_P1 430420 I06 PBMC \n", - "3 70117_20230210MM1_P1 430420 J06 PBMC \n", - "4 70117_20230210MM1_P1 430420 B07 PBMC \n", - ".. ... ... ... ... \n", - "149 70117_20230210MM1_P1 430420 O05 PBMC \n", - "150 70117_20230210MM1_P1 430420 O10 PBMC \n", - "151 70117_20230210MM1_P1 430420 O11 PBMC \n", - "152 70117_20230210MM1_P1 430420 B12 PBMC \n", - "153 70117_20230210MM1_P1 430420 I12 PBMC \n", - "\n", - " incubation inducer inhibitor inhibitor_concentration_value \\\n", - "0 6_h DMSO 0.025 \n", - "1 6_h DMSO 0.025 \n", - "2 6_h DMSO 0.025 \n", - "3 6_h DMSO 0.025 \n", - "4 6_h DMSO 0.025 \n", - ".. ... ... ... \n", - "149 6_h Media_ctr NaN \n", - "150 6_h Media_ctr NaN \n", - "151 6_h Media NaN \n", - "152 6_h Media_ctr NaN \n", - "153 6_h Media_ctr NaN \n", - "\n", - " inhibitor_concentration_unit inhibitor_concentration inducer1 ... \\\n", - "0 % 0.030 DMSO ... \n", - "1 % 0.030 DMSO ... \n", - "2 % 0.030 DMSO ... \n", - "3 % 0.030 DMSO ... \n", - "4 % 0.030 DMSO ... \n", - ".. ... ... ... ... \n", - "149 nan 0.0 media_ctr ... \n", - "150 nan 0.0 media_ctr ... \n", - "151 nan 0.0 media_ctr ... \n", - "152 nan 0.0 media_ctr ... \n", - "153 nan 0.0 media_ctr ... \n", - "\n", - " VEGF-D [NSU] VEGFR-1 [NSU] WISP-1 (CCN4) [NSU] XCL1 (Lymphotactin) [NSU] \\\n", - "0 0.258834 0.238358 0.524276 0.250670 \n", - "1 0.381170 0.168645 0.455092 0.228752 \n", - "2 0.182956 0.263281 0.213596 0.064645 \n", - "3 0.582053 0.087565 0.140992 0.234191 \n", - "4 0.264141 0.296782 0.541689 0.167078 \n", - ".. ... ... ... ... \n", - "149 0.275941 0.312566 0.286031 0.288358 \n", - "150 0.450715 0.178011 0.621119 0.229238 \n", - "151 0.308965 0.268730 0.613026 0.254080 \n", - "152 0.161322 0.296984 0.625991 0.297158 \n", - "153 0.367450 0.248619 0.404964 0.290474 \n", - "\n", - " Treatment Dose oneb_Treatment_Dose_Inhibitor_Dose \\\n", - "0 DMSO 0.100_% DMSO_0.100_%_DMSO_0.025_% \n", - "1 DMSO 0.100_% DMSO_0.100_%_DMSO_0.025_% \n", - "2 DMSO 0.100_% DMSO_0.100_%_DMSO_0.025_% \n", - "3 DMSO 0.100_% DMSO_0.100_%_DMSO_0.025_% \n", - "4 DMSO 0.100_% DMSO_0.100_%_DMSO_0.025_% \n", - ".. ... ... ... \n", - "149 media_ctr 0.0_nan media_ctr_0.0_0_Media_ctr_0.0_0 \n", - "150 media_ctr 0.0_nan media_ctr_0.0_0_Media_ctr_0.0_0 \n", - "151 media_ctr 0.0_nan media_ctr_0.0_0_Media_0.0_0 \n", - "152 media_ctr 0.0_nan media_ctr_0.0_0_Media_ctr_0.0_0 \n", - "153 media_ctr 0.0_nan media_ctr_0.0_0_Media_ctr_0.0_0 \n", - "\n", - " twob_Treatment_Dose_Inhibitor_Dose threeb_Treatment_Dose_Inhibitor_Dose \\\n", - "0 DMSO_DMSO_0.100_% DMSO__0.100_%__DMSO_0.030 \n", - "1 DMSO_DMSO_0.100_% DMSO__0.100_%__DMSO_0.030 \n", - "2 DMSO_DMSO_0.100_% DMSO__0.100_%__DMSO_0.030 \n", - "3 DMSO_DMSO_0.100_% DMSO__0.100_%__DMSO_0.030 \n", - "4 DMSO_DMSO_0.100_% DMSO__0.100_%__DMSO_0.030 \n", - ".. ... ... \n", - "149 media_ctr_Media_ctr_0.0_nan media_ctr__0.0_nan__Media_ctr_0.0 \n", - "150 media_ctr_Media_ctr_0.0_nan media_ctr__0.0_nan__Media_ctr_0.0 \n", - "151 media_ctr_Media_0.0_nan media_ctr__0.0_nan__Media_0.0 \n", - "152 media_ctr_Media_ctr_0.0_nan media_ctr__0.0_nan__Media_ctr_0.0 \n", - "153 media_ctr_Media_ctr_0.0_nan media_ctr__0.0_nan__Media_ctr_0.0 \n", - "\n", - " fourb_Treatment_Dose_Inhibitor_Dose \n", - "0 DMSO__0.100_%__DMSO__0.030 \n", - "1 DMSO__0.100_%__DMSO__0.030 \n", - "2 DMSO__0.100_%__DMSO__0.030 \n", - "3 DMSO__0.100_%__DMSO__0.030 \n", - "4 DMSO__0.100_%__DMSO__0.030 \n", - ".. ... \n", - "149 media_ctr__0.0_nan__Media_ctr__0.0 \n", - "150 media_ctr__0.0_nan__Media_ctr__0.0 \n", - "151 media_ctr__0.0_nan__Media__0.0 \n", - "152 media_ctr__0.0_nan__Media_ctr__0.0 \n", - "153 media_ctr__0.0_nan__Media_ctr__0.0 \n", - "\n", - "[154 rows x 218 columns]" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# rename columns\n", - "df = df.rename(\n", - " columns={\n", - " \"position_x\": \"Metadata_Well\",\n", - " \"oneb_Treatment_Dose_Inhibitor_Dose\": \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\",\n", - " }\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# out paths\n", - "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/secretome/\")\n", - "map_out_dir.mkdir(exist_ok=True, parents=True)\n", - "\n", - "# regular data output\n", - "# saving to csv\n", - "regular_feat_map_path = pathlib.Path(map_out_dir / \"mAP_scores_regular_treatment.csv\")\n", - "\n", - "# shuffled data output\n", - "shuffled_feat_map_path = pathlib.Path(map_out_dir / \"mAP_scores_shuffled_treatment.csv\")\n", - "\n", - "# shuffled feature space output\n", - "shuffled_feat_space_map_path = pathlib.Path(\n", - " map_out_dir / \"mAP_scores_shuffled_feature_space_treatment.csv\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Clean up data" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "37\n" - ] - } - ], - "source": [ - "# keep columns that contain Metdata and ['NSU']\n", - "df = df.filter(regex=\"Metadata|NSU\")\n", - "df.head()\n", - "\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].unique()\n", - "# replace values in the oneb_Metadata_Treatment_Dose_Inhibitor_Dose column\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\n", - " \"Flagellin_0.100_ug_per_ml_DMSO_0.000_%\", \"Flagellin_0.100_ug_per_ml_DMSO_0.025_%\"\n", - ")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\n", - " \"Flagellin_0.100_ug_per_ml_DMSO_0.0_%\", \"Flagellin_0.100_ug_per_ml_DMSO_0.025_%\"\n", - ")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\n", - " \"Flagellin_1.000_ug_per_ml_DMSO_0.0_%\", \"Flagellin_1.000_ug_per_ml_DMSO_0.025_%\"\n", - ")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\"Flagellin_1.000_0_DMSO_0.025_%\", \"Flagellin_1.000_ug_per_ml_DMSO_0.025_%\")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\n", - " \"Flagellin_1.000_ug_per_ml_DMSO_0.000_%\", \"Flagellin_1.000_ug_per_ml_DMSO_0.025_%\"\n", - ")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\"media_ctr_0.0_0_Media_0_0\", \"Media\")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\"media_ctr_0.0_0_Media_ctr_0.0_0\", \"Media\")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\n", - " \"Flagellin_1.000_0_Disulfiram_1.000_uM\",\n", - " \"Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM\",\n", - ")\n", - "df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = df[\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"\n", - "].replace(\"media_ctr_0.0_0_Media_0.0_0\", \"Media\")\n", - "print(len(df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].unique()))" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "# add apoptosis, pyroptosis and healthy columns to dataframe\n", - "df[\"Apoptosis\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in apoptosis_ground_truth,\n", - " axis=1,\n", - ")\n", - "df[\"Pyroptosis\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in pyroptosis_ground_truth,\n", - " axis=1,\n", - ")\n", - "df[\"Control\"] = df.apply(\n", - " lambda row: row[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - " in control_ground_truth,\n", - " axis=1,\n", - ")\n", - "\n", - "# merge apoptosis, pyroptosis, and healthy columns into one column\n", - "df[\"Metadata_labels\"] = df.apply(\n", - " lambda row: \"Apoptosis\"\n", - " if row[\"Apoptosis\"]\n", - " else \"Pyroptosis\"\n", - " if row[\"Pyroptosis\"]\n", - " else \"Control\",\n", - " axis=1,\n", - ")\n", - "# # drop apoptosis, pyroptosis, and healthy columns\n", - "df.drop(columns=[\"Apoptosis\", \"Pyroptosis\", \"Control\"], inplace=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# output directories\n", - "map_out_dir = pathlib.Path(\"../data/processed/mAP_scores/\")\n", - "map_out_dir.mkdir(parents=True, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP Pipeline Parameters" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The null size needs to be determined for the mAP pipeline. This is the size of the null class that is used to determine the mAP score." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "4\n" - ] - }, - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_Welloneb_Metadata_Treatment_Dose_Inhibitor_Dose
08DMSO_0.100_%_DMSO_0.025_%
14DMSO_0.100_%_DMSO_1.000_%
24DMSO_0.100_%_Z-VAD-FMK_100.000_uM
34DMSO_0.100_%_Z-VAD-FMK_30.000_uM
44Disulfiram_0.100_uM_DMSO_0.025_%
54Disulfiram_1.000_uM_DMSO_0.025_%
64Disulfiram_2.500_uM_DMSO_0.025_%
74Flagellin_0.100_ug_per_ml_DMSO_0.025_%
84Flagellin_1.000_ug_per_ml_DMSO_0.025_%
94Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM
104H2O2_100.000_nM_DMSO_0.025_%
114H2O2_100.000_uM_DMSO_0.025_%
124H2O2_100.000_uM_Disulfiram_1.000_uM
134H2O2_100.000_uM_Z-VAD-FMK_100.000_uM
144LPS_0.010_ug_per_ml_DMSO_0.025_%
154LPS_0.100_ug_per_ml_DMSO_0.025_%
164LPS_1.000_ug_per_ml_DMSO_0.025_%
174LPS_10.000_ug_per_ml_DMSO_0.025_%
184LPS_10.000_ug_per_ml_Disulfiram_0.100_uM
194LPS_10.000_ug_per_ml_Disulfiram_1.000_uM
204LPS_10.000_ug_per_ml_Disulfiram_2.500_uM
214LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM
224LPS_100.000_ug_per_ml_DMSO_0.025_%
234LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0....
244LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0...
254LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulf...
264LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...
274LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0....
284LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...
294LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO...
304LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_...
316Media
324Thapsigargin_1.000_uM_DMSO_0.025_%
334Thapsigargin_10.000_uM_DMSO_0.025_%
344Topotecan_10.000_nM_DMSO_0.025_%
354Topotecan_20.000_nM_DMSO_0.025_%
364Topotecan_5.000_nM_DMSO_0.025_%
\n", - "
" - ], - "text/plain": [ - " Metadata_Well oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "0 8 DMSO_0.100_%_DMSO_0.025_%\n", - "1 4 DMSO_0.100_%_DMSO_1.000_%\n", - "2 4 DMSO_0.100_%_Z-VAD-FMK_100.000_uM\n", - "3 4 DMSO_0.100_%_Z-VAD-FMK_30.000_uM\n", - "4 4 Disulfiram_0.100_uM_DMSO_0.025_%\n", - "5 4 Disulfiram_1.000_uM_DMSO_0.025_%\n", - "6 4 Disulfiram_2.500_uM_DMSO_0.025_%\n", - "7 4 Flagellin_0.100_ug_per_ml_DMSO_0.025_%\n", - "8 4 Flagellin_1.000_ug_per_ml_DMSO_0.025_%\n", - "9 4 Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM\n", - "10 4 H2O2_100.000_nM_DMSO_0.025_%\n", - "11 4 H2O2_100.000_uM_DMSO_0.025_%\n", - "12 4 H2O2_100.000_uM_Disulfiram_1.000_uM\n", - "13 4 H2O2_100.000_uM_Z-VAD-FMK_100.000_uM\n", - "14 4 LPS_0.010_ug_per_ml_DMSO_0.025_%\n", - "15 4 LPS_0.100_ug_per_ml_DMSO_0.025_%\n", - "16 4 LPS_1.000_ug_per_ml_DMSO_0.025_%\n", - "17 4 LPS_10.000_ug_per_ml_DMSO_0.025_%\n", - "18 4 LPS_10.000_ug_per_ml_Disulfiram_0.100_uM\n", - "19 4 LPS_10.000_ug_per_ml_Disulfiram_1.000_uM\n", - "20 4 LPS_10.000_ug_per_ml_Disulfiram_2.500_uM\n", - "21 4 LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM\n", - "22 4 LPS_100.000_ug_per_ml_DMSO_0.025_%\n", - "23 4 LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0....\n", - "24 4 LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0...\n", - "25 4 LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulf...\n", - "26 4 LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-...\n", - "27 4 LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0....\n", - "28 4 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_...\n", - "29 4 LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO...\n", - "30 4 LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_...\n", - "31 6 Media\n", - "32 4 Thapsigargin_1.000_uM_DMSO_0.025_%\n", - "33 4 Thapsigargin_10.000_uM_DMSO_0.025_%\n", - "34 4 Topotecan_10.000_nM_DMSO_0.025_%\n", - "35 4 Topotecan_20.000_nM_DMSO_0.025_%\n", - "36 4 Topotecan_5.000_nM_DMSO_0.025_%" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tmp = (\n", - " df.groupby([\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"])\n", - " .count()\n", - " .reset_index()[[\"Metadata_Well\", \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]]\n", - ")\n", - "# get the Pyroptosis number of Metadata_Well\n", - "# get the counts of each oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "min_count = tmp[\"Metadata_Well\"].min()\n", - "print(min_count)\n", - "tmp" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[('Control', 'Pyroptosis'),\n", - " ('Control', 'Apoptosis'),\n", - " ('Pyroptosis', 'Apoptosis')]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# generate the permutations of cell death labels via itertools\n", - "pos_samby_permutations = list(itertools.combinations(df[\"Metadata_labels\"].unique(), 2))\n", - "pos_samby_permutations" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "pos_sameby = [\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"]\n", - "pos_diffby = [\"Metadata_Well\"]\n", - "\n", - "neg_sameby = [\"Metadata_labels\"]\n", - "neg_diffby = [\n", - " \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\",\n", - "]\n", - "\n", - "null_size = min_count\n", - "batch_size = 1\n", - "\n", - "# number of resampling\n", - "n_resamples = 10" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP analysis for non-shuffled data" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "results_df = pd.DataFrame(\n", - " columns=[\n", - " \"Metadata_Well\",\n", - " \"Metadata_labels\",\n", - " \"average_precision\",\n", - " \"p_value\",\n", - " \"n_pos_pairs\",\n", - " \"n_total_pairs\",\n", - " \"shuffled\",\n", - " \"comparison\",\n", - " ]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "644b1a07ce9c491495279e9be9d9578d", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/130 [00:00\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparisononeb_Metadata_Treatment_Dose_Inhibitor_Dose
0B06Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
1C06Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
2I06Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
3J06Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
4B07Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
\n", - "" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 B06 Control 1.0 1.0 7.0 \n", - "1 C06 Control 1.0 1.0 7.0 \n", - "2 I06 Control 1.0 1.0 7.0 \n", - "3 J06 Control 1.0 1.0 7.0 \n", - "4 B07 Control 1.0 1.0 7.0 \n", - "\n", - " n_total_pairs shuffled \\\n", - "0 7.0 non-shuffled \n", - "1 7.0 non-shuffled \n", - "2 7.0 non-shuffled \n", - "3 7.0 non-shuffled \n", - "4 7.0 non-shuffled \n", - "\n", - " comparison \\\n", - "0 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "1 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "2 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "3 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "4 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose \n", - "0 DMSO_0.100_%_DMSO_0.025_% \n", - "1 DMSO_0.100_%_DMSO_0.025_% \n", - "2 DMSO_0.100_%_DMSO_0.025_% \n", - "3 DMSO_0.100_%_DMSO_0.025_% \n", - "4 DMSO_0.100_%_DMSO_0.025_% " - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "for i in df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].unique():\n", - "\n", - " # manually get treatment\n", - " tmp = df[\n", - " df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].str.contains(i)\n", - " ].reset_index(drop=True)\n", - " # get the label\n", - " label = tmp[\"Metadata_labels\"].unique().tolist()[0]\n", - " # add all labels to the df except for the LPS treatment label\n", - " tmp1 = df[~df[\"Metadata_labels\"].str.contains(label)].reset_index(drop=True)\n", - " # concat tmp and tmp1\n", - " tmp1 = pd.concat([tmp, tmp1]).reset_index(drop=True)\n", - "\n", - " # drop rows that contain the label\n", - " _pos_samby_permutations = [x for x in pos_samby_permutations if label in x]\n", - "\n", - " for j in _pos_samby_permutations:\n", - " tmp1 = tmp1[tmp1[\"Metadata_labels\"].isin(j)].reset_index(drop=True)\n", - "\n", - " # spliting metadata and raw feature values\n", - " logging.info(\"splitting data set into metadata and raw feature values\")\n", - " df_meta, df_feats = utils.split_data(tmp1)\n", - " df_feats = np.array(df_feats)\n", - " try:\n", - " # execute pipeline on negative control with trianing dataset with cp features\n", - "\n", - " logging.info(f\"Running pipeline on CP features using phenotype\")\n", - " result = run_pipeline(\n", - " meta=df_meta,\n", - " feats=df_feats,\n", - " pos_sameby=pos_sameby,\n", - " pos_diffby=pos_diffby,\n", - " neg_sameby=neg_sameby,\n", - " neg_diffby=neg_diffby,\n", - " batch_size=batch_size,\n", - " null_size=null_size,\n", - " )\n", - "\n", - " result[\"shuffled\"] = \"non-shuffled\"\n", - " comparison = i\n", - " comparison = comparison + \"_\" + \"_vs_\".join(j)\n", - "\n", - " result[\"comparison\"] = comparison\n", - "\n", - " except ZeroDivisionError as e:\n", - " logging.warning(f\"{e} captured on phenotye:. Skipping\")\n", - "\n", - " # concatenating all datasets\n", - " results_df = pd.concat([results_df, result], ignore_index=True)\n", - "results_df.to_csv(regular_feat_map_path, index=False)\n", - "results_df.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### mAP analysis for shuffled data (Phenotype)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "results_df = pd.DataFrame(\n", - " columns=[\n", - " \"Metadata_Well\",\n", - " \"Metadata_labels\",\n", - " \"average_precision\",\n", - " \"p_value\",\n", - " \"n_pos_pairs\",\n", - " \"n_total_pairs\",\n", - " \"shuffled\",\n", - " \"comparison\",\n", - " ]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2250c95daeb3497a81a66f2feab3700f", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/130 [00:00\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparisononeb_Metadata_Treatment_Dose_Inhibitor_Dose
0B06Control1.0000001.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
1C06Control1.0000001.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
2I06Control1.0000001.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
3J06Control1.0000001.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
4B07Control1.0000001.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%
..............................
5715C11Pyroptosis0.0437230.63.067.0non-shuffledMedia_Control_vs_PyroptosisLPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_...
5716J02Pyroptosis0.0551590.43.067.0non-shuffledMedia_Control_vs_PyroptosisLPS_100.000_ug_per_ml_DMSO_0.025_%
5717J03Pyroptosis0.0594740.43.067.0non-shuffledMedia_Control_vs_PyroptosisLPS_100.000_ug_per_ml_DMSO_0.025_%
5718J08Pyroptosis0.0916350.43.067.0non-shuffledMedia_Control_vs_PyroptosisLPS_100.000_ug_per_ml_DMSO_0.025_%
5719J09Pyroptosis0.0429410.63.067.0non-shuffledMedia_Control_vs_PyroptosisLPS_100.000_ug_per_ml_DMSO_0.025_%
\n", - "

5720 rows \u00d7 9 columns

\n", - "" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 B06 Control 1.000000 1.0 7.0 \n", - "1 C06 Control 1.000000 1.0 7.0 \n", - "2 I06 Control 1.000000 1.0 7.0 \n", - "3 J06 Control 1.000000 1.0 7.0 \n", - "4 B07 Control 1.000000 1.0 7.0 \n", - "... ... ... ... ... ... \n", - "5715 C11 Pyroptosis 0.043723 0.6 3.0 \n", - "5716 J02 Pyroptosis 0.055159 0.4 3.0 \n", - "5717 J03 Pyroptosis 0.059474 0.4 3.0 \n", - "5718 J08 Pyroptosis 0.091635 0.4 3.0 \n", - "5719 J09 Pyroptosis 0.042941 0.6 3.0 \n", - "\n", - " n_total_pairs shuffled \\\n", - "0 7.0 non-shuffled \n", - "1 7.0 non-shuffled \n", - "2 7.0 non-shuffled \n", - "3 7.0 non-shuffled \n", - "4 7.0 non-shuffled \n", - "... ... ... \n", - "5715 67.0 non-shuffled \n", - "5716 67.0 non-shuffled \n", - "5717 67.0 non-shuffled \n", - "5718 67.0 non-shuffled \n", - "5719 67.0 non-shuffled \n", - "\n", - " comparison \\\n", - "0 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "1 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "2 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "3 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "4 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "... ... \n", - "5715 Media_Control_vs_Pyroptosis \n", - "5716 Media_Control_vs_Pyroptosis \n", - "5717 Media_Control_vs_Pyroptosis \n", - "5718 Media_Control_vs_Pyroptosis \n", - "5719 Media_Control_vs_Pyroptosis \n", - "\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose \n", - "0 DMSO_0.100_%_DMSO_0.025_% \n", - "1 DMSO_0.100_%_DMSO_0.025_% \n", - "2 DMSO_0.100_%_DMSO_0.025_% \n", - "3 DMSO_0.100_%_DMSO_0.025_% \n", - "4 DMSO_0.100_%_DMSO_0.025_% \n", - "... ... \n", - "5715 LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_... \n", - "5716 LPS_100.000_ug_per_ml_DMSO_0.025_% \n", - "5717 LPS_100.000_ug_per_ml_DMSO_0.025_% \n", - "5718 LPS_100.000_ug_per_ml_DMSO_0.025_% \n", - "5719 LPS_100.000_ug_per_ml_DMSO_0.025_% \n", - "\n", - "[5720 rows x 9 columns]" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "for i in df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].unique():\n", - "\n", - " # manually get treatment\n", - " tmp = df[\n", - " df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"].str.contains(i)\n", - " ].reset_index(drop=True)\n", - " # get the label\n", - " label = tmp[\"Metadata_labels\"].unique().tolist()[0]\n", - " # add all labels to the df except for the LPS treatment label\n", - " tmp1 = df[~df[\"Metadata_labels\"].str.contains(label)].reset_index(drop=True)\n", - " # concat tmp and tmp1\n", - " tmp1 = pd.concat([tmp, tmp1]).reset_index(drop=True)\n", - "\n", - " # drop rows that contain the label\n", - " _pos_samby_permutations = [x for x in pos_samby_permutations if label in x]\n", - "\n", - " for j in _pos_samby_permutations:\n", - " tmp1 = tmp1[tmp1[\"Metadata_labels\"].isin(j)].reset_index(drop=True)\n", - "\n", - " # spliting metadata and raw feature values\n", - " logging.info(\"splitting data set into metadata and raw feature values\")\n", - " df_meta, df_feats = utils.split_data(tmp1)\n", - " df_feats = np.array(df_feats)\n", - " seed = np.random.randint(0, 100)\n", - "\n", - " # shuffling the features, this will overwrite the generated feature space from above with the shuffled one\n", - " df_feats = shuffle_features(feature_vals=df_feats, seed=seed)\n", - "\n", - " try:\n", - " # execute pipeline on negative control with trianing dataset with cp features\n", - "\n", - " logging.info(f\"Running pipeline on CP features using phenotype\")\n", - " result = run_pipeline(\n", - " meta=df_meta,\n", - " feats=df_feats,\n", - " pos_sameby=pos_sameby,\n", - " pos_diffby=pos_diffby,\n", - " neg_sameby=neg_sameby,\n", - " neg_diffby=neg_diffby,\n", - " batch_size=batch_size,\n", - " null_size=null_size,\n", - " )\n", - "\n", - " result[\"shuffled\"] = \"shuffled\"\n", - " comparison = i\n", - " comparison = comparison + \"_\" + \"_vs_\".join(j)\n", - "\n", - " result[\"comparison\"] = comparison\n", - "\n", - " except ZeroDivisionError as e:\n", - " logging.warning(f\"{e} captured on phenotye:. Skipping\")\n", - "\n", - " # concatenating all datasets\n", - " results_df = pd.concat([results_df, result], ignore_index=True)\n", - "\n", - "# saving to csv\n", - "results_df.to_csv(shuffled_feat_space_map_path, index=False)\n", - "results_df" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "map", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.2" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.mAP/notebooks/7.aggregate_map_scores_secretome_treatment.ipynb b/9.mAP/notebooks/7.aggregate_map_scores_secretome_treatment.ipynb deleted file mode 100644 index 9a0ca5fa3..000000000 --- a/9.mAP/notebooks/7.aggregate_map_scores_secretome_treatment.ipynb +++ /dev/null @@ -1,482 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pathlib\n", - "import warnings\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "import plotly.express as px\n", - "from copairs.map import aggregate\n", - "\n", - "warnings.filterwarnings(\"ignore\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# Directories\n", - "processed_data_dir = pathlib.Path(\"../data/processed/\")\n", - "sc_ap_scores_dir = (processed_data_dir / \"mAP_scores/secretome\").resolve()\n", - "agg_sc_ap_scores_dir = (processed_data_dir / \"aggregate_mAPs/secretome\").resolve()\n", - "agg_sc_ap_scores_dir.mkdir(parents=True, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Preparing the dataset\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparisononeb_Metadata_Treatment_Dose_Inhibitor_Dosefile
0B06Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%mAP_scores_regular_treatment
1C06Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%mAP_scores_regular_treatment
2I06Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%mAP_scores_regular_treatment
3J06Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%mAP_scores_regular_treatment
4B07Control1.01.07.07.0non-shuffledDMSO_0.100_%_DMSO_0.025_%_Control_vs_PyroptosisDMSO_0.100_%_DMSO_0.025_%mAP_scores_regular_treatment
\n", - "
" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs \\\n", - "0 B06 Control 1.0 1.0 7.0 \n", - "1 C06 Control 1.0 1.0 7.0 \n", - "2 I06 Control 1.0 1.0 7.0 \n", - "3 J06 Control 1.0 1.0 7.0 \n", - "4 B07 Control 1.0 1.0 7.0 \n", - "\n", - " n_total_pairs shuffled \\\n", - "0 7.0 non-shuffled \n", - "1 7.0 non-shuffled \n", - "2 7.0 non-shuffled \n", - "3 7.0 non-shuffled \n", - "4 7.0 non-shuffled \n", - "\n", - " comparison \\\n", - "0 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "1 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "2 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "3 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "4 DMSO_0.100_%_DMSO_0.025_%_Control_vs_Pyroptosis \n", - "\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose file \n", - "0 DMSO_0.100_%_DMSO_0.025_% mAP_scores_regular_treatment \n", - "1 DMSO_0.100_%_DMSO_0.025_% mAP_scores_regular_treatment \n", - "2 DMSO_0.100_%_DMSO_0.025_% mAP_scores_regular_treatment \n", - "3 DMSO_0.100_%_DMSO_0.025_% mAP_scores_regular_treatment \n", - "4 DMSO_0.100_%_DMSO_0.025_% mAP_scores_regular_treatment " - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_files = list(sc_ap_scores_dir.glob(\"*.csv\"))\n", - "# get the files that contain the string class\n", - "class_files = [file for file in all_files if \"treatment\" in file.stem]\n", - "mAPs = []\n", - "for file in class_files:\n", - " df = pd.read_csv(file)\n", - " df[\"file\"] = file.stem\n", - " mAPs.append(df)\n", - "# single-cell mAP scores\n", - "mAPs = pd.concat(mAPs)\n", - "mAPs.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# grabbing all cp features (regular, feature shuffled and labeled shuffled)\n", - "reg_sc_mAPs = mAPs.loc[mAPs[\"shuffled\"] == \"non-shuffled\"]\n", - "shuffled_feat_sc_mAPs = mAPs.loc[mAPs[\"shuffled\"] == \"features_shuffled\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
oneb_Metadata_Treatment_Dose_Inhibitor_Doseshuffledsampling_error
0DMSO_0.100_%_DMSO_0.025_%non-shuffled0.007552
1phenotypes_shuffledphenotypes_shuffledphenotypes_shuffled
2DMSO_0.100_%_DMSO_1.000_%non-shuffled0.020573
3phenotypes_shuffledphenotypes_shuffledphenotypes_shuffled
4DMSO_0.100_%_Z-VAD-FMK_100.000_uMnon-shuffled0.017628
\n", - "
" - ], - "text/plain": [ - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose shuffled \\\n", - "0 DMSO_0.100_%_DMSO_0.025_% non-shuffled \n", - "1 phenotypes_shuffled phenotypes_shuffled \n", - "2 DMSO_0.100_%_DMSO_1.000_% non-shuffled \n", - "3 phenotypes_shuffled phenotypes_shuffled \n", - "4 DMSO_0.100_%_Z-VAD-FMK_100.000_uM non-shuffled \n", - "\n", - " sampling_error \n", - "0 0.007552 \n", - "1 phenotypes_shuffled \n", - "2 0.020573 \n", - "3 phenotypes_shuffled \n", - "4 0.017628 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# grouping dataframe based on phenotype levels, feature and feature types\n", - "df_group = mAPs.groupby(by=[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\", \"shuffled\"])\n", - "\n", - "# calculating sampling error\n", - "sampling_error_df = []\n", - "for name, df in df_group:\n", - " pheno, shuffled_type = name\n", - "\n", - " # caclulating sampling error\n", - " avg_percision = df[\"average_precision\"].values\n", - " sampling_error = np.std(avg_percision) / np.sqrt(len(avg_percision))\n", - "\n", - " sampling_error_df.append([pheno, shuffled_type, sampling_error])\n", - "cols = [\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\", \"shuffled\", \"sampling_error\"]\n", - "sampling_error_df = pd.DataFrame(sampling_error_df, columns=cols)\n", - "\n", - "sampling_error_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
oneb_Metadata_Treatment_Dose_Inhibitor_Dosemean_average_precisionnlog10pvalueq_valuenlog10qvalueabove_p_thresholdabove_q_thresholdshuffled
0DMSO_0.100_%_DMSO_0.025_%0.181305-0.000001.0-0.00000FalseFalsenon-shuffled
0DMSO_0.100_%_DMSO_0.025_%0.041839-0.000001.0-0.00000FalseFalsephenotype_shuffled
0DMSO_0.100_%_DMSO_1.000_%0.475383-0.000001.0-0.00000FalseFalsenon-shuffled
0DMSO_0.100_%_DMSO_1.000_%0.0608120.698970.20.69897FalseFalsephenotype_shuffled
0DMSO_0.100_%_Z-VAD-FMK_100.000_uM0.396818-0.000001.0-0.00000FalseFalsenon-shuffled
\n", - "
" - ], - "text/plain": [ - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose mean_average_precision \\\n", - "0 DMSO_0.100_%_DMSO_0.025_% 0.181305 \n", - "0 DMSO_0.100_%_DMSO_0.025_% 0.041839 \n", - "0 DMSO_0.100_%_DMSO_1.000_% 0.475383 \n", - "0 DMSO_0.100_%_DMSO_1.000_% 0.060812 \n", - "0 DMSO_0.100_%_Z-VAD-FMK_100.000_uM 0.396818 \n", - "\n", - " nlog10pvalue q_value nlog10qvalue above_p_threshold above_q_threshold \\\n", - "0 -0.00000 1.0 -0.00000 False False \n", - "0 -0.00000 1.0 -0.00000 False False \n", - "0 -0.00000 1.0 -0.00000 False False \n", - "0 0.69897 0.2 0.69897 False False \n", - "0 -0.00000 1.0 -0.00000 False False \n", - "\n", - " shuffled \n", - "0 non-shuffled \n", - "0 phenotype_shuffled \n", - "0 non-shuffled \n", - "0 phenotype_shuffled \n", - "0 non-shuffled " - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Generating aggregate scores with a threshold p-value of 0.05\n", - "mAP_dfs = []\n", - "for name, df in tuple(\n", - " mAPs.groupby(by=[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\", \"shuffled\"])\n", - "):\n", - " agg_df = aggregate(\n", - " df, sameby=[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"], threshold=0.05\n", - " )\n", - " agg_df[\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"] = name[0]\n", - " agg_df[\"shuffled\"] = name[1]\n", - " mAP_dfs.append(agg_df)\n", - "\n", - "mAP_dfs = pd.concat(mAP_dfs)\n", - "mAP_dfs.to_csv(agg_sc_ap_scores_dir / \"mAP_scores_treatment.csv\", index=False)\n", - "mAP_dfs.head()" - ] - } - ], - "metadata": { - "interpreter": { - "hash": "2a7bc4b693a428e685bdbc198b90c0fe2d737ece3fda25b7a5d0fc6f41082281" - }, - "kernelspec": { - "display_name": "Python 3.12.0 ('map')", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.mAP/notebooks/8.visualize_map_scores.ipynb b/9.mAP/notebooks/8.visualize_map_scores.ipynb deleted file mode 100644 index dcdbdb28a..000000000 --- a/9.mAP/notebooks/8.visualize_map_scores.ipynb +++ /dev/null @@ -1,1926 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [], - "source": [ - "suppressPackageStartupMessages(suppressWarnings(library(ggplot2)))\n", - "suppressPackageStartupMessages(suppressWarnings(library(RColorBrewer)))\n", - "suppressPackageStartupMessages(suppressWarnings(library(dplyr)))\n", - "suppressPackageStartupMessages(suppressWarnings(library(tidyr)))\n", - "source(\"../../figures/utils/figure_themes.r\")\n", - "\n", - "width <- 8\n", - "height <- 6\n", - "options(repr.plot.width=width, repr.plot.height=height)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [], - "source": [ - "# set path to the data morphology\n", - "# class\n", - "df_morphology_class_path <- file.path(\"..\",\"data\",\"processed\",\"aggregate_mAPs\",\"morphology\",\"mAP_scores_class.csv\")\n", - "reg_df_morphology_class_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_regular_class.csv\")\n", - "shuffled_morphology_class_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_shuffled_feature_space_class.csv\")\n", - "# treatment \n", - "treatment_df_morphology_treatment_path <- file.path(\"..\",\"data\",\"processed\",\"aggregate_mAPs\",\"morphology\",\"mAP_scores_treatment.csv\")\n", - "reg_df_morphology_treatment_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_regular_treatment.csv\")\n", - "shuffled_morphology_treatment_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_shuffled_feature_space_treatment.csv\")\n", - "\n", - "# set path to the secretome data\n", - "# class\n", - "df_secretome_class_path <- file.path(\"..\",\"data\",\"processed\",\"aggregate_mAPs\",\"secretome\",\"mAP_scores_class.csv\")\n", - "reg_df_secretome_class_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_regular_class.csv\")\n", - "shuffled_secretome_class_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_shuffled_feature_space_class.csv\")\n", - "# treatment\n", - "treatment_df_secretome_treatment_path <- file.path(\"..\",\"data\",\"processed\",\"aggregate_mAPs\",\"secretome\",\"mAP_scores_treatment.csv\")\n", - "reg_df_secretome_treatment_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_regular_treatment.csv\")\n", - "shuffled_secretome_treatment_path <- file.path(\"..\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_shuffled_feature_space_treatment.csv\")\n", - "\n", - "# read in the data\n", - "df_morphology_class <- read.csv(df_morphology_class_path)\n", - "reg_df_morphology_class <- read.csv(reg_df_morphology_class_path)\n", - "shuffled_morphology_class <- read.csv(shuffled_morphology_class_path)\n", - "\n", - "df_morphology_treatment <- read.csv(treatment_df_morphology_treatment_path)\n", - "reg_df_morphology_treatment <- read.csv(reg_df_morphology_treatment_path)\n", - "shuffled_morphology_treatment <- read.csv(shuffled_morphology_treatment_path)\n", - "\n", - "df_secretome_class <- read.csv(df_secretome_class_path)\n", - "reg_df_secretome_class <- read.csv(reg_df_secretome_class_path)\n", - "shuffled_secretome_class <- read.csv(shuffled_secretome_class_path)\n", - "\n", - "df_secretome_treatment <- read.csv(treatment_df_secretome_treatment_path)\n", - "reg_df_secretome_treatment <- read.csv(reg_df_secretome_treatment_path)\n", - "shuffled_secretome_treatment <- read.csv(shuffled_secretome_treatment_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
  1. 'non-shuffled'
  2. 'shuffled'
\n" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item 'non-shuffled'\n", - "\\item 'shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. 'non-shuffled'\n", - "2. 'shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] \"non-shuffled\" \"shuffled\" " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
  1. 'non-shuffled'
  2. 'shuffled'
\n" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item 'non-shuffled'\n", - "\\item 'shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. 'non-shuffled'\n", - "2. 'shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] \"non-shuffled\" \"shuffled\" " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
  1. 'non-shuffled'
  2. 'shuffled'
\n" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item 'non-shuffled'\n", - "\\item 'shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. 'non-shuffled'\n", - "2. 'shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] \"non-shuffled\" \"shuffled\" " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
  1. 'non-shuffled'
  2. 'shuffled'
\n" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item 'non-shuffled'\n", - "\\item 'shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. 'non-shuffled'\n", - "2. 'shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] \"non-shuffled\" \"shuffled\" " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "unique(df_morphology_class$shuffled)\n", - "unique(df_morphology_treatment$shuffled)\n", - "unique(df_secretome_class$shuffled)\n", - "unique(df_secretome_treatment$shuffled)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [], - "source": [ - "levels_list <- c(\n", - " 'Media',\n", - " 'DMSO_0.100_%_DMSO_0.025_%',\n", - " 'DMSO_0.100_%_DMSO_1.000_%',\n", - " 'DMSO_0.100_%_Z-VAD-FMK_30.000_uM',\n", - " 'DMSO_0.100_%_Z-VAD-FMK_100.000_uM',\n", - "\n", - " 'Disulfiram_0.100_uM_DMSO_0.025_%',\n", - " 'Disulfiram_1.000_uM_DMSO_0.025_%',\n", - " 'Disulfiram_2.500_uM_DMSO_0.025_%',\n", - " \n", - " 'Flagellin_0.100_ug_per_ml_DMSO_0.025_%',\n", - " 'Flagellin_1.000_ug_per_ml_DMSO_0.025_%',\n", - " 'Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM',\n", - " \n", - " 'LPS_0.010_ug_per_ml_DMSO_0.025_%',\n", - " 'LPS_0.100_ug_per_ml_DMSO_0.025_%',\n", - " 'LPS_1.000_ug_per_ml_DMSO_0.025_%',\n", - "\n", - " 'LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM',\n", - " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM',\n", - "\n", - " 'LPS_10.000_ug_per_ml_DMSO_0.025_%',\n", - " 'LPS_10.000_ug_per_ml_Disulfiram_0.100_uM',\n", - " 'LPS_10.000_ug_per_ml_Disulfiram_1.000_uM',\n", - " 'LPS_10.000_ug_per_ml_Disulfiram_2.500_uM',\n", - " 'LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM',\n", - " \n", - " 'LPS_100.000_ug_per_ml_DMSO_0.025_%',\n", - " 'LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%',\n", - "\n", - " 'H2O2_100.000_nM_DMSO_0.025_%',\n", - " 'H2O2_100.000_uM_DMSO_0.025_%',\n", - " 'H2O2_100.000_uM_Disulfiram_1.000_uM',\n", - " 'H2O2_100.000_uM_Z-VAD-FMK_100.000_uM',\n", - " 'Thapsigargin_1.000_uM_DMSO_0.025_%',\n", - " 'Thapsigargin_10.000_uM_DMSO_0.025_%',\n", - "\n", - " 'Topotecan_5.000_nM_DMSO_0.025_%', \n", - " 'Topotecan_10.000_nM_DMSO_0.025_%',\n", - " 'Topotecan_20.000_nM_DMSO_0.025_%'\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Clean the class data" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [], - "source": [ - "# declare the shuffled column as a factor\n", - "# replace the values in the shuffled column\n", - "# declare the shuffled column as a factor\n", - "# replace the values in the shuffled column\n", - "df_morphology_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", df_morphology_class$shuffled)\n", - "df_morphology_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", df_morphology_class$shuffled)\n", - "df_morphology_class$shuffled <- factor(df_morphology_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "df_morphology_class$Metadata_labels <- factor(df_morphology_class$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", - "\n", - "df_secretome_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", df_secretome_class$shuffled)\n", - "df_secretome_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", df_secretome_class$shuffled)\n", - "df_secretome_class$shuffled <- factor(df_secretome_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "df_secretome_class$Metadata_labels <- factor(df_secretome_class$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", - "\n", - "df_morphology_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", df_morphology_treatment$shuffled)\n", - "df_morphology_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", df_morphology_treatment$shuffled)\n", - "df_morphology_treatment$shuffled <- factor(df_morphology_treatment$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)\n", - "\n", - "df_secretome_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", df_secretome_treatment$shuffled)\n", - "df_secretome_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", df_secretome_treatment$shuffled)\n", - "df_secretome_treatment$shuffled <- factor(df_secretome_treatment$shuffled, levels = c(\"Non-shuffled\", \"Shuffled\"))\n", - "df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
  1. Non-shuffled
  2. Shuffled
\n", - "\n", - "
\n", - "\t\n", - "\t\tLevels:\n", - "\t\n", - "\t\n", - "\t
  1. 'Non-shuffled'
  2. 'Shuffled'
\n", - "
" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item Non-shuffled\n", - "\\item Shuffled\n", - "\\end{enumerate*}\n", - "\n", - "\\emph{Levels}: \\begin{enumerate*}\n", - "\\item 'Non-shuffled'\n", - "\\item 'Shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. Non-shuffled\n", - "2. Shuffled\n", - "\n", - "\n", - "\n", - "**Levels**: 1. 'Non-shuffled'\n", - "2. 'Shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] Non-shuffled Shuffled \n", - "Levels: Non-shuffled Shuffled" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
  1. Non-shuffled
  2. Shuffled
\n", - "\n", - "
\n", - "\t\n", - "\t\tLevels:\n", - "\t\n", - "\t\n", - "\t
  1. 'Non-shuffled'
  2. 'Shuffled'
\n", - "
" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item Non-shuffled\n", - "\\item Shuffled\n", - "\\end{enumerate*}\n", - "\n", - "\\emph{Levels}: \\begin{enumerate*}\n", - "\\item 'Non-shuffled'\n", - "\\item 'Shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. Non-shuffled\n", - "2. Shuffled\n", - "\n", - "\n", - "\n", - "**Levels**: 1. 'Non-shuffled'\n", - "2. 'Shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] Non-shuffled Shuffled \n", - "Levels: Non-shuffled Shuffled" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
  1. Non-shuffled
  2. Shuffled
\n", - "\n", - "
\n", - "\t\n", - "\t\tLevels:\n", - "\t\n", - "\t\n", - "\t
  1. 'Non-shuffled'
  2. 'Shuffled'
\n", - "
" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item Non-shuffled\n", - "\\item Shuffled\n", - "\\end{enumerate*}\n", - "\n", - "\\emph{Levels}: \\begin{enumerate*}\n", - "\\item 'Non-shuffled'\n", - "\\item 'Shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. Non-shuffled\n", - "2. Shuffled\n", - "\n", - "\n", - "\n", - "**Levels**: 1. 'Non-shuffled'\n", - "2. 'Shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] Non-shuffled Shuffled \n", - "Levels: Non-shuffled Shuffled" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
  1. Non-shuffled
  2. Shuffled
\n", - "\n", - "
\n", - "\t\n", - "\t\tLevels:\n", - "\t\n", - "\t\n", - "\t
  1. 'Non-shuffled'
  2. 'Shuffled'
\n", - "
" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item Non-shuffled\n", - "\\item Shuffled\n", - "\\end{enumerate*}\n", - "\n", - "\\emph{Levels}: \\begin{enumerate*}\n", - "\\item 'Non-shuffled'\n", - "\\item 'Shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. Non-shuffled\n", - "2. Shuffled\n", - "\n", - "\n", - "\n", - "**Levels**: 1. 'Non-shuffled'\n", - "2. 'Shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] Non-shuffled Shuffled \n", - "Levels: Non-shuffled Shuffled" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "unique(df_morphology_class$shuffled)\n", - "unique(df_morphology_treatment$shuffled)\n", - "unique(df_secretome_class$shuffled)\n", - "unique(df_secretome_treatment$shuffled)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [], - "source": [ - "width <- 10\n", - "height <- 5\n", - "options(repr.plot.width=width, repr.plot.height=height)\n", - "# define the barplot function\n", - "barplot_function <- function(df, x,title, y_label, x_label, legend_title){\n", - " x <- sym(x)\n", - " barplot <- (\n", - " ggplot(df, aes(x=!!x, y=mean_average_precision, fill=shuffled))\n", - " + geom_bar(stat=\"identity\", position=\"dodge\")\n", - " + labs(x=x_label, y=y_label)\n", - " # legend title\n", - " + scale_fill_discrete(name=legend_title)\n", - " + theme_bw()\n", - " + ylim(0,1)\n", - " + ggtitle(title)\n", - " + figure_theme\n", - " )\n", - " return(barplot)\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 300, - "width": 600 - } - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 300, - "width": 600 - } - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 300, - "width": 600 - } - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 300, - "width": 600 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "barplot_morphology_class <- barplot_function(df_morphology_class, \"Metadata_labels\",\"Morphology class\", \"Mean average precision\", \"Class\", \"Shuffle type\")\n", - "barplot_morphology_treatment <- barplot_function(df_morphology_treatment, \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\",\"Morphology treatment\", \"Mean average precision\", \"Treatment\", \"Shuffle type\")\n", - "barplot_secretome_class <- barplot_function(df_secretome_class, \"Metadata_labels\",\"Secretome class\", \"Mean average precision\", \"Class\", \"Shuffle type\")\n", - "barplot_secretome_treatment <- barplot_function(df_secretome_treatment, \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\",\"Secretome treatment\", \"Mean average precision\", \"Treatment\", \"Shuffle type\")\n", - "\n", - "barplot_morphology_class\n", - "barplot_morphology_treatment\n", - "barplot_secretome_class\n", - "barplot_secretome_treatment\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Clean the single well data" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [], - "source": [ - "# combine the dataframes\n", - "all_df_morphology_class <- rbind(reg_df_morphology_class, shuffled_morphology_class)\n", - "all_df_morphology_treatment <- rbind(reg_df_morphology_treatment, shuffled_morphology_treatment)\n", - "all_df_secretome_class <- rbind(reg_df_secretome_class, shuffled_secretome_class)\n", - "all_df_secretome_treatment <- rbind(reg_df_secretome_treatment, shuffled_secretome_treatment)\n", - "\n", - "all_df_morphology_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_morphology_class$shuffled)\n", - "all_df_morphology_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_morphology_class$shuffled)\n", - "all_df_morphology_class$shuffled <- factor(all_df_morphology_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_morphology_class$Metadata_labels <- factor(all_df_morphology_class$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", - "\n", - "all_df_secretome_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_secretome_class$shuffled)\n", - "all_df_secretome_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_secretome_class$shuffled)\n", - "all_df_secretome_class$shuffled <- factor(all_df_secretome_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "\n", - "all_df_morphology_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_morphology_treatment$shuffled)\n", - "all_df_morphology_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_morphology_treatment$shuffled)\n", - "all_df_morphology_treatment$shuffled <- factor(all_df_morphology_treatment$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)\n", - "\n", - "all_df_secretome_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_secretome_treatment$shuffled)\n", - "all_df_secretome_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_secretome_treatment$shuffled)\n", - "all_df_secretome_treatment$shuffled <- factor(all_df_secretome_treatment$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
  1. Non-shuffled
  2. Shuffled
\n", - "\n", - "
\n", - "\t\n", - "\t\tLevels:\n", - "\t\n", - "\t\n", - "\t
  1. 'Non-shuffled'
  2. 'Shuffled'
\n", - "
" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item Non-shuffled\n", - "\\item Shuffled\n", - "\\end{enumerate*}\n", - "\n", - "\\emph{Levels}: \\begin{enumerate*}\n", - "\\item 'Non-shuffled'\n", - "\\item 'Shuffled'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. Non-shuffled\n", - "2. Shuffled\n", - "\n", - "\n", - "\n", - "**Levels**: 1. 'Non-shuffled'\n", - "2. 'Shuffled'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] Non-shuffled Shuffled \n", - "Levels: Non-shuffled Shuffled" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "unique(all_df_secretome_class$shuffled)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## mAP Scatter compare plot" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 8
Metadata_WellMetadata_labelsaverage_precisionp_valuen_pos_pairsn_total_pairsshuffledcomparison
<chr><fct><dbl><dbl><dbl><dbl><fct><chr>
1B02Pyroptosis0.63419970.0151515264145Non-shuffledPyroptosis_vs_Control
2B03Pyroptosis0.52119950.1212121364145Non-shuffledPyroptosis_vs_Control
3B04Pyroptosis0.84482230.0151515264145Non-shuffledPyroptosis_vs_Control
4B05Pyroptosis0.83862220.0151515264145Non-shuffledPyroptosis_vs_Control
5B06Control 0.77310190.0151515280145Non-shuffledPyroptosis_vs_Control
6B07Control 0.66855340.0303030380145Non-shuffledPyroptosis_vs_Control
\n" - ], - "text/latex": [ - "A data.frame: 6 × 8\n", - "\\begin{tabular}{r|llllllll}\n", - " & Metadata\\_Well & Metadata\\_labels & average\\_precision & p\\_value & n\\_pos\\_pairs & n\\_total\\_pairs & shuffled & comparison\\\\\n", - " & & & & & & & & \\\\\n", - "\\hline\n", - "\t1 & B02 & Pyroptosis & 0.6341997 & 0.01515152 & 64 & 145 & Non-shuffled & Pyroptosis\\_vs\\_Control\\\\\n", - "\t2 & B03 & Pyroptosis & 0.5211995 & 0.12121213 & 64 & 145 & Non-shuffled & Pyroptosis\\_vs\\_Control\\\\\n", - "\t3 & B04 & Pyroptosis & 0.8448223 & 0.01515152 & 64 & 145 & Non-shuffled & Pyroptosis\\_vs\\_Control\\\\\n", - "\t4 & B05 & Pyroptosis & 0.8386222 & 0.01515152 & 64 & 145 & Non-shuffled & Pyroptosis\\_vs\\_Control\\\\\n", - "\t5 & B06 & Control & 0.7731019 & 0.01515152 & 80 & 145 & Non-shuffled & Pyroptosis\\_vs\\_Control\\\\\n", - "\t6 & B07 & Control & 0.6685534 & 0.03030303 & 80 & 145 & Non-shuffled & Pyroptosis\\_vs\\_Control\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 8\n", - "\n", - "| | Metadata_Well <chr> | Metadata_labels <fct> | average_precision <dbl> | p_value <dbl> | n_pos_pairs <dbl> | n_total_pairs <dbl> | shuffled <fct> | comparison <chr> |\n", - "|---|---|---|---|---|---|---|---|---|\n", - "| 1 | B02 | Pyroptosis | 0.6341997 | 0.01515152 | 64 | 145 | Non-shuffled | Pyroptosis_vs_Control |\n", - "| 2 | B03 | Pyroptosis | 0.5211995 | 0.12121213 | 64 | 145 | Non-shuffled | Pyroptosis_vs_Control |\n", - "| 3 | B04 | Pyroptosis | 0.8448223 | 0.01515152 | 64 | 145 | Non-shuffled | Pyroptosis_vs_Control |\n", - "| 4 | B05 | Pyroptosis | 0.8386222 | 0.01515152 | 64 | 145 | Non-shuffled | Pyroptosis_vs_Control |\n", - "| 5 | B06 | Control | 0.7731019 | 0.01515152 | 80 | 145 | Non-shuffled | Pyroptosis_vs_Control |\n", - "| 6 | B07 | Control | 0.6685534 | 0.03030303 | 80 | 145 | Non-shuffled | Pyroptosis_vs_Control |\n", - "\n" - ], - "text/plain": [ - " Metadata_Well Metadata_labels average_precision p_value n_pos_pairs\n", - "1 B02 Pyroptosis 0.6341997 0.01515152 64 \n", - "2 B03 Pyroptosis 0.5211995 0.12121213 64 \n", - "3 B04 Pyroptosis 0.8448223 0.01515152 64 \n", - "4 B05 Pyroptosis 0.8386222 0.01515152 64 \n", - "5 B06 Control 0.7731019 0.01515152 80 \n", - "6 B07 Control 0.6685534 0.03030303 80 \n", - " n_total_pairs shuffled comparison \n", - "1 145 Non-shuffled Pyroptosis_vs_Control\n", - "2 145 Non-shuffled Pyroptosis_vs_Control\n", - "3 145 Non-shuffled Pyroptosis_vs_Control\n", - "4 145 Non-shuffled Pyroptosis_vs_Control\n", - "5 145 Non-shuffled Pyroptosis_vs_Control\n", - "6 145 Non-shuffled Pyroptosis_vs_Control" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "head(all_df_morphology_class)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 4
shuffledMetadata_labelsmorphology_apsecretome_ap
<fct><fct><dbl><dbl>
1Non-shuffledApoptosis0.87675070.9821429
2Non-shuffledApoptosis0.87675071.0000000
3Non-shuffledApoptosis0.87675071.0000000
4Non-shuffledApoptosis0.87675071.0000000
5Non-shuffledApoptosis0.87675071.0000000
6Non-shuffledApoptosis0.87675070.3432313
\n" - ], - "text/latex": [ - "A data.frame: 6 × 4\n", - "\\begin{tabular}{r|llll}\n", - " & shuffled & Metadata\\_labels & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & Apoptosis & 0.8767507 & 0.9821429\\\\\n", - "\t2 & Non-shuffled & Apoptosis & 0.8767507 & 1.0000000\\\\\n", - "\t3 & Non-shuffled & Apoptosis & 0.8767507 & 1.0000000\\\\\n", - "\t4 & Non-shuffled & Apoptosis & 0.8767507 & 1.0000000\\\\\n", - "\t5 & Non-shuffled & Apoptosis & 0.8767507 & 1.0000000\\\\\n", - "\t6 & Non-shuffled & Apoptosis & 0.8767507 & 0.3432313\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 4\n", - "\n", - "| | shuffled <fct> | Metadata_labels <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Apoptosis | 0.8767507 | 0.9821429 |\n", - "| 2 | Non-shuffled | Apoptosis | 0.8767507 | 1.0000000 |\n", - "| 3 | Non-shuffled | Apoptosis | 0.8767507 | 1.0000000 |\n", - "| 4 | Non-shuffled | Apoptosis | 0.8767507 | 1.0000000 |\n", - "| 5 | Non-shuffled | Apoptosis | 0.8767507 | 1.0000000 |\n", - "| 6 | Non-shuffled | Apoptosis | 0.8767507 | 0.3432313 |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels morphology_ap secretome_ap\n", - "1 Non-shuffled Apoptosis 0.8767507 0.9821429 \n", - "2 Non-shuffled Apoptosis 0.8767507 1.0000000 \n", - "3 Non-shuffled Apoptosis 0.8767507 1.0000000 \n", - "4 Non-shuffled Apoptosis 0.8767507 1.0000000 \n", - "5 Non-shuffled Apoptosis 0.8767507 1.0000000 \n", - "6 Non-shuffled Apoptosis 0.8767507 0.3432313 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# cobine the dfs\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_morphology_class <- all_df_morphology_class[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\")]\n", - "# rename the average_precision column to moprhology_ap\n", - "colnames(subset_morphology_class)[colnames(subset_morphology_class)==\"average_precision\"] <- \"morphology_ap\"\n", - "\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_secretome_class <- all_df_secretome_class[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\")]\n", - "# rename the average_precision column to secretome_ap\n", - "colnames(subset_secretome_class)[colnames(subset_secretome_class)==\"average_precision\"] <- \"secretome_ap\"\n", - "\n", - "# merge the dataframes\n", - "merged_df <- merge(subset_morphology_class, subset_secretome_class, by=c(\"shuffled\", \"Metadata_labels\"))\n", - "head(merged_df)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 5
shuffledMetadata_labelsmorphology_apsecretome_apgroup
<fct><fct><dbl><dbl><fct>
Non-shuffledControl 0.77344800.9565076NA
Shuffled Control 0.73659330.7065620NA
Non-shuffledApoptosis 0.68183770.8657605Non-shuffled\n", - "Apoptosis
Shuffled Apoptosis 0.10984660.1867049NA
Non-shuffledPyroptosis0.80494380.9286838NA
Shuffled Pyroptosis0.67459020.6924981NA
\n" - ], - "text/latex": [ - "A data.frame: 6 × 5\n", - "\\begin{tabular}{lllll}\n", - " shuffled & Metadata\\_labels & morphology\\_ap & secretome\\_ap & group\\\\\n", - " & & & & \\\\\n", - "\\hline\n", - "\t Non-shuffled & Control & 0.7734480 & 0.9565076 & NA \\\\\n", - "\t Shuffled & Control & 0.7365933 & 0.7065620 & NA \\\\\n", - "\t Non-shuffled & Apoptosis & 0.6818377 & 0.8657605 & Non-shuffled\n", - "Apoptosis\\\\\n", - "\t Shuffled & Apoptosis & 0.1098466 & 0.1867049 & NA \\\\\n", - "\t Non-shuffled & Pyroptosis & 0.8049438 & 0.9286838 & NA \\\\\n", - "\t Shuffled & Pyroptosis & 0.6745902 & 0.6924981 & NA \\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 5\n", - "\n", - "| shuffled <fct> | Metadata_labels <fct> | morphology_ap <dbl> | secretome_ap <dbl> | group <fct> |\n", - "|---|---|---|---|---|\n", - "| Non-shuffled | Control | 0.7734480 | 0.9565076 | NA |\n", - "| Shuffled | Control | 0.7365933 | 0.7065620 | NA |\n", - "| Non-shuffled | Apoptosis | 0.6818377 | 0.8657605 | Non-shuffled\n", - "Apoptosis |\n", - "| Shuffled | Apoptosis | 0.1098466 | 0.1867049 | NA |\n", - "| Non-shuffled | Pyroptosis | 0.8049438 | 0.9286838 | NA |\n", - "| Shuffled | Pyroptosis | 0.6745902 | 0.6924981 | NA |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels morphology_ap secretome_ap\n", - "1 Non-shuffled Control 0.7734480 0.9565076 \n", - "2 Shuffled Control 0.7365933 0.7065620 \n", - "3 Non-shuffled Apoptosis 0.6818377 0.8657605 \n", - "4 Shuffled Apoptosis 0.1098466 0.1867049 \n", - "5 Non-shuffled Pyroptosis 0.8049438 0.9286838 \n", - "6 Shuffled Pyroptosis 0.6745902 0.6924981 \n", - " group \n", - "1 NA \n", - "2 NA \n", - "3 Non-shuffled\\nApoptosis\n", - "4 NA \n", - "5 NA \n", - "6 NA " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# aggregate the data by shuffled and Metadata_labels\n", - "merged_agg <- aggregate(. ~ shuffled + Metadata_labels, data=merged_df, FUN=mean)\n", - "# combine the shuffled and Metadata_labels columns\n", - "merged_agg$group <- paste(merged_agg$shuffled, merged_agg$Metadata_labels, sep=\"_\")\n", - "# change the text in the group column\n", - "merged_agg$group <- gsub(\"Non-shuffled Control\", \"Non-shuffled\\nControl\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Control\", \"Shuffled\\nControl\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Non-shuffled_Apoptosis\", \"Non-shuffled\\nApoptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Apoptosis\", \"Shuffled\\nApoptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Non-shuffled Pyroptosis\", \"Non-shuffled\\nPyroptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Pyroptosis\", \"Shuffled\\nPyroptosis\", merged_agg$group)\n", - "# make the group column a factor\n", - "merged_agg$group <- factor(\n", - " merged_agg$group, \n", - " levels = c(\n", - " \"Non-shuffled\\nControl\", \n", - " \"Shuffled features\\nControl\", \n", - " \"Shuffled phenotypes\\nControl\", \n", - "\n", - " \"Non-shuffled\\nApoptosis\", \n", - " \"Shuffled features\\nApoptosis\", \n", - " \"Shuffled phenotypes\\nApoptosis\",\n", - " \n", - " \"Non-shuffled\\nPyroptosis\",\n", - " \"Shuffled features\\nPyroptosis\", \n", - " \"Shuffled phenotypes\\nPyroptosis\"))\n", - "\n", - "merged_agg" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 360, - "width": 480 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "width <- 8\n", - "height <- 6\n", - "options(repr.plot.width=width, repr.plot.height=height)\n", - "# plot the data\n", - "scatter_compare <- (\n", - " ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled))\n", - " + geom_point(size=3, alpha=1)\n", - " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", - " + theme_bw()\n", - " + ggtitle(\"Comparison of mAP scores\")\n", - " + ylim(0,1)\n", - " + xlim(0,1)\n", - " # Change the legend title\n", - " # change the legend shape\n", - " + scale_shape_manual(\n", - " name=\"Shuffle type\",\n", - " labels=c(\n", - " \"Non-shuffled\", \n", - " \"Shuffled features\", \n", - " \"Shuffled phenotypes\"\n", - " ),\n", - " values=c(19, 17, 15)\n", - " )\n", - " + scale_color_manual(\n", - " name=\"Class\",\n", - " labels=c(\n", - " \"Control\", \n", - " \"Apoptosis\", \n", - " \"Pyroptosis\"\n", - " ),\n", - " values=c(\n", - " brewer.pal(3, \"Dark2\")[2],\n", - " brewer.pal(3, \"Dark2\")[1],\n", - " brewer.pal(3, \"Dark2\")[3]\n", - " )\n", - ")\n", - " + figure_theme\n", - " # add y = x line\n", - " + geom_abline(intercept = 0, slope = 1, linetype=\"dashed\")\n", - "\n", - ")\n", - "scatter_compare" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## mAP Scatter compare plot treatemnts\n" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 5
shuffledMetadata_labelsoneb_Metadata_Treatment_Dose_Inhibitor_Dosemorphology_apsecretome_ap
<fct><chr><fct><dbl><dbl>
1Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.79166671
2Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.79166671
3Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.79166671
4Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.79166671
5Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.79166671
6Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.79166671
\n" - ], - "text/latex": [ - "A data.frame: 6 × 5\n", - "\\begin{tabular}{r|lllll}\n", - " & shuffled & Metadata\\_labels & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7916667 & 1\\\\\n", - "\t2 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7916667 & 1\\\\\n", - "\t3 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7916667 & 1\\\\\n", - "\t4 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7916667 & 1\\\\\n", - "\t5 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7916667 & 1\\\\\n", - "\t6 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7916667 & 1\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 5\n", - "\n", - "| | shuffled <fct> | Metadata_labels <chr> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7916667 | 1 |\n", - "| 2 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7916667 | 1 |\n", - "| 3 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7916667 | 1 |\n", - "| 4 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7916667 | 1 |\n", - "| 5 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7916667 | 1 |\n", - "| 6 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7916667 | 1 |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "1 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "2 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "3 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "4 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "5 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "6 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - " morphology_ap secretome_ap\n", - "1 0.7916667 1 \n", - "2 0.7916667 1 \n", - "3 0.7916667 1 \n", - "4 0.7916667 1 \n", - "5 0.7916667 1 \n", - "6 0.7916667 1 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# cobine the dfs\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_morphology_treatment <- all_df_morphology_treatment[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\",\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\")]\n", - "# rename the average_precision column to moprhology_ap\n", - "colnames(subset_morphology_treatment)[colnames(subset_morphology_treatment)==\"average_precision\"] <- \"morphology_ap\"\n", - "\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_secretome_treatment <- all_df_secretome_treatment[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\",\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\")]\n", - "# rename the average_precision column to secretome_ap\n", - "colnames(subset_secretome_treatment)[colnames(subset_secretome_treatment)==\"average_precision\"] <- \"secretome_ap\"\n", - "\n", - "# merge the dataframes\n", - "merged_df <- merge(subset_morphology_treatment, subset_secretome_treatment, by=c(\"shuffled\", \"Metadata_labels\", \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"))\n", - "head(merged_df)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "\n", - " FALSE TRUE \n", - "226662 1818 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# get the number of points that are morphology = 1 and secretome = 1\n", - "counts <- table(merged_df$morphology_ap == 1 & merged_df$secretome_ap == 1)\n", - "counts" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 360, - "width": 480 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled\n", - "merged_agg <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels, data=merged_df, FUN=mean)\n", - "# scatter plot\n", - "scatter_compare_treatment <- (\n", - " ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled))\n", - " + geom_point(size=3, alpha=0.5)\n", - " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", - " + theme_bw()\n", - " + ggtitle(\"Comparison of mAP scores\")\n", - " + ylim(0,1)\n", - " + xlim(0,1)\n", - " # Change the legend title\n", - " # change the legend shape\n", - " + scale_shape_manual(\n", - " name=\"Shuffle type\",\n", - " labels=c(\n", - " \"Non-shuffled\", \n", - " \"Shuffled features\", \n", - " \"Shuffled phenotypes\"\n", - " ),\n", - " values=c(19, 17, 15)\n", - " )\n", - " + scale_color_manual(\n", - " name=\"Class\",\n", - " labels=c(\n", - " \"Control\", \n", - " \"Apoptosis\", \n", - " \"Pyroptosis\"\n", - " ),\n", - " values=c(\n", - " brewer.pal(3, \"Dark2\")[2],\n", - " brewer.pal(3, \"Dark2\")[1],\n", - " brewer.pal(3, \"Dark2\")[3]\n", - " )\n", - ")\n", - " + figure_theme\n", - " # add y = x line\n", - " + geom_abline(intercept = 0, slope = 1, linetype=\"dashed\", color = \"black\")\n", - ")\n", - "scatter_compare_treatment" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 5
shuffledoneb_Metadata_Treatment_Dose_Inhibitor_DoseMetadata_labelsmorphology_apsecretome_ap
<fct><fct><chr><dbl><dbl>
1Non-shuffledThapsigargin_1.000_uM_DMSO_0.025_% Apoptosis0.67837301.0000000
2Shuffled Thapsigargin_1.000_uM_DMSO_0.025_% Apoptosis0.56944441.0000000
3Non-shuffledThapsigargin_10.000_uM_DMSO_0.025_%Apoptosis1.00000001.0000000
4Shuffled Thapsigargin_10.000_uM_DMSO_0.025_%Apoptosis0.37319021.0000000
5Non-shuffledMedia Control 0.56524410.2921671
6Shuffled Media Control 0.51418410.1583530
\n" - ], - "text/latex": [ - "A data.frame: 6 × 5\n", - "\\begin{tabular}{r|lllll}\n", - " & shuffled & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & Metadata\\_labels & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & Apoptosis & 0.6783730 & 1.0000000\\\\\n", - "\t2 & Shuffled & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & Apoptosis & 0.5694444 & 1.0000000\\\\\n", - "\t3 & Non-shuffled & Thapsigargin\\_10.000\\_uM\\_DMSO\\_0.025\\_\\% & Apoptosis & 1.0000000 & 1.0000000\\\\\n", - "\t4 & Shuffled & Thapsigargin\\_10.000\\_uM\\_DMSO\\_0.025\\_\\% & Apoptosis & 0.3731902 & 1.0000000\\\\\n", - "\t5 & Non-shuffled & Media & Control & 0.5652441 & 0.2921671\\\\\n", - "\t6 & Shuffled & Media & Control & 0.5141841 & 0.1583530\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 5\n", - "\n", - "| | shuffled <fct> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <fct> | Metadata_labels <chr> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Thapsigargin_1.000_uM_DMSO_0.025_% | Apoptosis | 0.6783730 | 1.0000000 |\n", - "| 2 | Shuffled | Thapsigargin_1.000_uM_DMSO_0.025_% | Apoptosis | 0.5694444 | 1.0000000 |\n", - "| 3 | Non-shuffled | Thapsigargin_10.000_uM_DMSO_0.025_% | Apoptosis | 1.0000000 | 1.0000000 |\n", - "| 4 | Shuffled | Thapsigargin_10.000_uM_DMSO_0.025_% | Apoptosis | 0.3731902 | 1.0000000 |\n", - "| 5 | Non-shuffled | Media | Control | 0.5652441 | 0.2921671 |\n", - "| 6 | Shuffled | Media | Control | 0.5141841 | 0.1583530 |\n", - "\n" - ], - "text/plain": [ - " shuffled oneb_Metadata_Treatment_Dose_Inhibitor_Dose Metadata_labels\n", - "1 Non-shuffled Thapsigargin_1.000_uM_DMSO_0.025_% Apoptosis \n", - "2 Shuffled Thapsigargin_1.000_uM_DMSO_0.025_% Apoptosis \n", - "3 Non-shuffled Thapsigargin_10.000_uM_DMSO_0.025_% Apoptosis \n", - "4 Shuffled Thapsigargin_10.000_uM_DMSO_0.025_% Apoptosis \n", - "5 Non-shuffled Media Control \n", - "6 Shuffled Media Control \n", - " morphology_ap secretome_ap\n", - "1 0.6783730 1.0000000 \n", - "2 0.5694444 1.0000000 \n", - "3 1.0000000 1.0000000 \n", - "4 0.3731902 1.0000000 \n", - "5 0.5652441 0.2921671 \n", - "6 0.5141841 0.1583530 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "head(merged_agg)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
  1. 'Thapsigargin 1.0 uM'
  2. 'Thapsigargin 10.0 uM'
  3. 'Disulfiram 0.1 uM'
  4. 'Disulfiram 1.0 uM'
  5. 'Disulfiram 2.5 uM'
  6. 'DMSO 0.1%'
  7. 'Flagellin 0.1 ug/ml'
  8. 'H2O2 100.0 nM'
  9. 'H2O2 100.0 uM'
  10. 'LPS 10.0 ug/ml'
  11. 'LPS 1.0 ug/ml + Nigericin 10.0 uM'
  12. NA
  13. 'Topotecan 10.0 nM'
  14. 'Topotecan 20.0 nM'
  15. 'Topotecan 5.0 nM'
  16. 'Flagellin 1.0 ug/ml'
  17. 'LPS 0.01 ug/ml'
  18. 'LPS 0.1 ug/ml'
  19. 'LPS 1.0 ug/ml'
  20. 'LPS 100.0 ug/ml'
  21. 'LPS 1.0 ug/ml + Nigericin 1.0 uM'
  22. 'LPS 1.0 ug/ml + Nigericin 3.0 uM'
  23. 'LPS 100.0 ug/ml + Nigericin 1.0 uM'
  24. 'LPS 100.0 ug/ml + Nigericin 10.0 uM'
  25. 'LPS 100.0 ug/ml + Nigericin 3.0 uM'
\n" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item 'Thapsigargin 1.0 uM'\n", - "\\item 'Thapsigargin 10.0 uM'\n", - "\\item 'Disulfiram 0.1 uM'\n", - "\\item 'Disulfiram 1.0 uM'\n", - "\\item 'Disulfiram 2.5 uM'\n", - "\\item 'DMSO 0.1\\%'\n", - "\\item 'Flagellin 0.1 ug/ml'\n", - "\\item 'H2O2 100.0 nM'\n", - "\\item 'H2O2 100.0 uM'\n", - "\\item 'LPS 10.0 ug/ml'\n", - "\\item 'LPS 1.0 ug/ml + Nigericin 10.0 uM'\n", - "\\item NA\n", - "\\item 'Topotecan 10.0 nM'\n", - "\\item 'Topotecan 20.0 nM'\n", - "\\item 'Topotecan 5.0 nM'\n", - "\\item 'Flagellin 1.0 ug/ml'\n", - "\\item 'LPS 0.01 ug/ml'\n", - "\\item 'LPS 0.1 ug/ml'\n", - "\\item 'LPS 1.0 ug/ml'\n", - "\\item 'LPS 100.0 ug/ml'\n", - "\\item 'LPS 1.0 ug/ml + Nigericin 1.0 uM'\n", - "\\item 'LPS 1.0 ug/ml + Nigericin 3.0 uM'\n", - "\\item 'LPS 100.0 ug/ml + Nigericin 1.0 uM'\n", - "\\item 'LPS 100.0 ug/ml + Nigericin 10.0 uM'\n", - "\\item 'LPS 100.0 ug/ml + Nigericin 3.0 uM'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. 'Thapsigargin 1.0 uM'\n", - "2. 'Thapsigargin 10.0 uM'\n", - "3. 'Disulfiram 0.1 uM'\n", - "4. 'Disulfiram 1.0 uM'\n", - "5. 'Disulfiram 2.5 uM'\n", - "6. 'DMSO 0.1%'\n", - "7. 'Flagellin 0.1 ug/ml'\n", - "8. 'H2O2 100.0 nM'\n", - "9. 'H2O2 100.0 uM'\n", - "10. 'LPS 10.0 ug/ml'\n", - "11. 'LPS 1.0 ug/ml + Nigericin 10.0 uM'\n", - "12. NA\n", - "13. 'Topotecan 10.0 nM'\n", - "14. 'Topotecan 20.0 nM'\n", - "15. 'Topotecan 5.0 nM'\n", - "16. 'Flagellin 1.0 ug/ml'\n", - "17. 'LPS 0.01 ug/ml'\n", - "18. 'LPS 0.1 ug/ml'\n", - "19. 'LPS 1.0 ug/ml'\n", - "20. 'LPS 100.0 ug/ml'\n", - "21. 'LPS 1.0 ug/ml + Nigericin 1.0 uM'\n", - "22. 'LPS 1.0 ug/ml + Nigericin 3.0 uM'\n", - "23. 'LPS 100.0 ug/ml + Nigericin 1.0 uM'\n", - "24. 'LPS 100.0 ug/ml + Nigericin 10.0 uM'\n", - "25. 'LPS 100.0 ug/ml + Nigericin 3.0 uM'\n", - "\n", - "\n" - ], - "text/plain": [ - " [1] \"Thapsigargin 1.0 uM\" \"Thapsigargin 10.0 uM\" \n", - " [3] \"Disulfiram 0.1 uM\" \"Disulfiram 1.0 uM\" \n", - " [5] \"Disulfiram 2.5 uM\" \"DMSO 0.1%\" \n", - " [7] \"Flagellin 0.1 ug/ml\" \"H2O2 100.0 nM\" \n", - " [9] \"H2O2 100.0 uM\" \"LPS 10.0 ug/ml\" \n", - "[11] \"LPS 1.0 ug/ml + Nigericin 10.0 uM\" NA \n", - "[13] \"Topotecan 10.0 nM\" \"Topotecan 20.0 nM\" \n", - "[15] \"Topotecan 5.0 nM\" \"Flagellin 1.0 ug/ml\" \n", - "[17] \"LPS 0.01 ug/ml\" \"LPS 0.1 ug/ml\" \n", - "[19] \"LPS 1.0 ug/ml\" \"LPS 100.0 ug/ml\" \n", - "[21] \"LPS 1.0 ug/ml + Nigericin 1.0 uM\" \"LPS 1.0 ug/ml + Nigericin 3.0 uM\" \n", - "[23] \"LPS 100.0 ug/ml + Nigericin 1.0 uM\" \"LPS 100.0 ug/ml + Nigericin 10.0 uM\"\n", - "[25] \"LPS 100.0 ug/ml + Nigericin 3.0 uM\" " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
  1. 'DMSO 0.025%'
  2. 'DMSO 1.0%'
  3. 'Z-VAD-FMK 100.0 uM'
  4. 'Z-VAD-FMK 30.0 uM'
  5. 'Disulfiram 1.0 uM'
  6. 'Media'
  7. 'Disulfiram 0.1 uM'
  8. 'Disulfiram 2.5 uM'
\n" - ], - "text/latex": [ - "\\begin{enumerate*}\n", - "\\item 'DMSO 0.025\\%'\n", - "\\item 'DMSO 1.0\\%'\n", - "\\item 'Z-VAD-FMK 100.0 uM'\n", - "\\item 'Z-VAD-FMK 30.0 uM'\n", - "\\item 'Disulfiram 1.0 uM'\n", - "\\item 'Media'\n", - "\\item 'Disulfiram 0.1 uM'\n", - "\\item 'Disulfiram 2.5 uM'\n", - "\\end{enumerate*}\n" - ], - "text/markdown": [ - "1. 'DMSO 0.025%'\n", - "2. 'DMSO 1.0%'\n", - "3. 'Z-VAD-FMK 100.0 uM'\n", - "4. 'Z-VAD-FMK 30.0 uM'\n", - "5. 'Disulfiram 1.0 uM'\n", - "6. 'Media'\n", - "7. 'Disulfiram 0.1 uM'\n", - "8. 'Disulfiram 2.5 uM'\n", - "\n", - "\n" - ], - "text/plain": [ - "[1] \"DMSO 0.025%\" \"DMSO 1.0%\" \"Z-VAD-FMK 100.0 uM\"\n", - "[4] \"Z-VAD-FMK 30.0 uM\" \"Disulfiram 1.0 uM\" \"Media\" \n", - "[7] \"Disulfiram 0.1 uM\" \"Disulfiram 2.5 uM\" " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 7
shuffledMetadata_labelsoneb_Metadata_Treatment_Dose_Inhibitor_Doseinducerinhibitormorphology_apsecretome_ap
<fct><chr><chr><fct><fct><dbl><dbl>
1Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.79166671
2Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.79166671
3Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.79166671
4Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.79166671
5Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.79166671
6Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.79166671
\n" - ], - "text/latex": [ - "A data.frame: 6 × 7\n", - "\\begin{tabular}{r|lllllll}\n", - " & shuffled & Metadata\\_labels & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & inducer & inhibitor & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7916667 & 1\\\\\n", - "\t2 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7916667 & 1\\\\\n", - "\t3 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7916667 & 1\\\\\n", - "\t4 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7916667 & 1\\\\\n", - "\t5 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7916667 & 1\\\\\n", - "\t6 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7916667 & 1\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 7\n", - "\n", - "| | shuffled <fct> | Metadata_labels <chr> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <chr> | inducer <fct> | inhibitor <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7916667 | 1 |\n", - "| 2 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7916667 | 1 |\n", - "| 3 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7916667 | 1 |\n", - "| 4 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7916667 | 1 |\n", - "| 5 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7916667 | 1 |\n", - "| 6 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7916667 | 1 |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "1 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "2 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "3 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "4 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "5 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "6 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - " inducer inhibitor morphology_ap secretome_ap\n", - "1 Thapsigargin 1.0 uM DMSO 0.025% 0.7916667 1 \n", - "2 Thapsigargin 1.0 uM DMSO 0.025% 0.7916667 1 \n", - "3 Thapsigargin 1.0 uM DMSO 0.025% 0.7916667 1 \n", - "4 Thapsigargin 1.0 uM DMSO 0.025% 0.7916667 1 \n", - "5 Thapsigargin 1.0 uM DMSO 0.025% 0.7916667 1 \n", - "6 Thapsigargin 1.0 uM DMSO 0.025% 0.7916667 1 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "merged_df <- merged_df %>%\n", - " mutate(oneb_Metadata_Treatment_Dose_Inhibitor_Dose = case_when(\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_DMSO_0.025_%' ~ \"DMSO 0.1% - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_DMSO_1.000_%' ~ \"DMSO 0.1% - DMSO 1.0%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_Z-VAD-FMK_100.000_uM' ~ \"DMSO 0.1% - Z-VAD-FMK 100.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_Z-VAD-FMK_30.000_uM' ~ \"DMSO 0.1% - Z-VAD-FMK 30.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_DMSO_0.025_%' ~ \"Flagellin 1.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM' ~ \"Flagellin 1.0 ug/ml - Disulfiram 1.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_0.010_ug_per_ml_DMSO_0.025_%' ~ \"LPS 0.01 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_0.100_ug_per_ml_DMSO_0.025_%' ~ \"LPS 0.1 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_0.100_ug_per_ml_DMSO_0.0_%' ~ \"Flagellin 0.1 ug/ml - DMSO 0.0%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_0.100_ug_per_ml_DMSO_0.025_%' ~ \"Flagellin 0.1 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_0.100_uM_DMSO_0.025_%' ~ \"Disulfiram 0.1 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - Disulfiram 1.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - Z-VAD-FMK 100.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_1.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_DMSO_0.0_%' ~ \"Flagellin 1.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_1.000_uM_DMSO_0.025_%' ~ \"Disulfiram 1.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Thapsigargin_1.000_uM_DMSO_0.025_%' ~ \"Thapsigargin 1.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_10.000_nM_DMSO_0.025_%' ~ \"Topotecan 10.0 nM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 10.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_0.100_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 0.1 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_1.000_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 1.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_2.500_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 2.5 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM' ~ \"LPS 10.0 ug/ml - Z-VAD-FMK 100.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Thapsigargin_10.000_uM_DMSO_0.025_%' ~ \"Thapsigargin 10.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_nM_DMSO_0.025_%' ~ \"H2O2 100.0 nM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_100.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_DMSO_0.025_%' ~ \"H2O2 100.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_Disulfiram_1.000_uM' ~ \"H2O2 100.0 uM - Disulfiram 1.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_Z-VAD-FMK_100.000_uM' ~ \"H2O2 100.0 uM - Z-VAD-FMK 100.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_2.500_uM_DMSO_0.025_%' ~ \"Disulfiram 2.5 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_20.000_nM_DMSO_0.025_%' ~ \"Topotecan 20.0 nM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_5.000_nM_DMSO_0.025_%' ~ \"Topotecan 5.0 nM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ \"Media ctr 0.0 0\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='media_ctr_0.0_0_Media_0.0_0' ~ \"Media ctr 0.0 0\"\n", - " ))\n", - " # replace Media ctr 0.0 0 with Media\n", - "merged_df$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- gsub(\"Media ctr 0.0 0\", \"Media\", merged_df$oneb_Metadata_Treatment_Dose_Inhibitor_Dose)\n", - "\n", - "# split the oneb_Metadata_Treatment_Dose_Inhibitor_Dose into two columns by the \" - \" delimiter\n", - "merged_df <- merged_df %>%\n", - " separate(oneb_Metadata_Treatment_Dose_Inhibitor_Dose, c(\"inducer\", \"inhibitor\"), sep = \" - \", remove = FALSE)\n", - "\n", - "unique(merged_df$inducer)\n", - "# replace the inhibitor NA with Media\n", - "merged_df$inhibitor <- ifelse(is.na(merged_df$inhibitor), \"Media\", merged_df$inhibitor)\n", - "unique(merged_df$inhibitor)\n", - "\n", - "# make the group_treatment column a factor\n", - "merged_df$inducer <- factor(\n", - " merged_df$inducer,\n", - " levels = c(\n", - " 'Media',\n", - " 'DMSO 0.1%',\n", - "\n", - " 'Flagellin 0.1 ug/ml',\n", - " 'Flagellin 1.0 ug/ml',\n", - "\n", - " 'LPS 0.01 ug/ml',\n", - " 'LPS 0.1 ug/ml',\n", - " 'LPS 1.0 ug/ml',\n", - " 'LPS 10.0 ug/ml',\n", - " 'LPS 100.0 ug/ml',\n", - "\n", - " 'LPS 1.0 ug/ml + Nigericin 1.0 uM',\n", - " 'LPS 1.0 ug/ml + Nigericin 3.0 uM',\n", - " 'LPS 1.0 ug/ml + Nigericin 10.0 uM',\n", - "\n", - " 'LPS 100.0 ug/ml + Nigericin 1.0 uM',\n", - " 'LPS 100.0 ug/ml + Nigericin 3.0 uM',\n", - " 'LPS 100.0 ug/ml + Nigericin 10.0 uM',\n", - "\n", - " 'H2O2 100.0 nM',\n", - " 'H2O2 100.0 uM',\n", - "\n", - " 'Disulfiram 0.1 uM',\n", - " 'Disulfiram 1.0 uM',\n", - " 'Disulfiram 2.5 uM',\n", - "\n", - " 'Thapsigargin 1.0 uM',\n", - " 'Thapsigargin 10.0 uM',\n", - "\n", - " 'Topotecan 5.0 nM',\n", - " 'Topotecan 10.0 nM',\n", - " 'Topotecan 20.0 nM'\n", - " )\n", - ")\n", - "\n", - "# make the group_treatment column a factor\n", - "merged_df$inhibitor <- factor(\n", - " merged_df$inhibitor,\n", - " levels = c(\n", - " 'Media',\n", - " 'DMSO 0.025%',\n", - " 'DMSO 1.0%',\n", - "\n", - " 'Disulfiram 0.1 uM',\n", - " 'Disulfiram 1.0 uM',\n", - " 'Disulfiram 2.5 uM',\n", - "\n", - " 'Z-VAD-FMK 30.0 uM',\n", - " 'Z-VAD-FMK 100.0 uM'\n", - " )\n", - ")\n", - "head(merged_df)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 7
shuffledoneb_Metadata_Treatment_Dose_Inhibitor_DoseMetadata_labelsinducerinhibitormorphology_apsecretome_ap
<fct><chr><chr><fct><fct><dbl><dbl>
1Non-shuffledDMSO 0.1% - DMSO 0.025% Control DMSO 0.1% DMSO 0.025%0.68772380.2060009
2Shuffled DMSO 0.1% - DMSO 0.025% Control DMSO 0.1% DMSO 0.025%0.68429130.1808192
3Non-shuffledFlagellin 0.1 ug/ml - DMSO 0.025%Control Flagellin 0.1 ug/mlDMSO 0.025%0.97916671.0000000
4Shuffled Flagellin 0.1 ug/ml - DMSO 0.025%Control Flagellin 0.1 ug/mlDMSO 0.025%0.34899290.1219735
5Non-shuffledFlagellin 1.0 ug/ml - DMSO 0.025%PyroptosisFlagellin 1.0 ug/mlDMSO 0.025%0.70138890.7706767
6Shuffled Flagellin 1.0 ug/ml - DMSO 0.025%PyroptosisFlagellin 1.0 ug/mlDMSO 0.025%0.44103840.1403870
\n" - ], - "text/latex": [ - "A data.frame: 6 × 7\n", - "\\begin{tabular}{r|lllllll}\n", - " & shuffled & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & Metadata\\_labels & inducer & inhibitor & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & DMSO 0.1\\% - DMSO 0.025\\% & Control & DMSO 0.1\\% & DMSO 0.025\\% & 0.6877238 & 0.2060009\\\\\n", - "\t2 & Shuffled & DMSO 0.1\\% - DMSO 0.025\\% & Control & DMSO 0.1\\% & DMSO 0.025\\% & 0.6842913 & 0.1808192\\\\\n", - "\t3 & Non-shuffled & Flagellin 0.1 ug/ml - DMSO 0.025\\% & Control & Flagellin 0.1 ug/ml & DMSO 0.025\\% & 0.9791667 & 1.0000000\\\\\n", - "\t4 & Shuffled & Flagellin 0.1 ug/ml - DMSO 0.025\\% & Control & Flagellin 0.1 ug/ml & DMSO 0.025\\% & 0.3489929 & 0.1219735\\\\\n", - "\t5 & Non-shuffled & Flagellin 1.0 ug/ml - DMSO 0.025\\% & Pyroptosis & Flagellin 1.0 ug/ml & DMSO 0.025\\% & 0.7013889 & 0.7706767\\\\\n", - "\t6 & Shuffled & Flagellin 1.0 ug/ml - DMSO 0.025\\% & Pyroptosis & Flagellin 1.0 ug/ml & DMSO 0.025\\% & 0.4410384 & 0.1403870\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 7\n", - "\n", - "| | shuffled <fct> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <chr> | Metadata_labels <chr> | inducer <fct> | inhibitor <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | DMSO 0.1% - DMSO 0.025% | Control | DMSO 0.1% | DMSO 0.025% | 0.6877238 | 0.2060009 |\n", - "| 2 | Shuffled | DMSO 0.1% - DMSO 0.025% | Control | DMSO 0.1% | DMSO 0.025% | 0.6842913 | 0.1808192 |\n", - "| 3 | Non-shuffled | Flagellin 0.1 ug/ml - DMSO 0.025% | Control | Flagellin 0.1 ug/ml | DMSO 0.025% | 0.9791667 | 1.0000000 |\n", - "| 4 | Shuffled | Flagellin 0.1 ug/ml - DMSO 0.025% | Control | Flagellin 0.1 ug/ml | DMSO 0.025% | 0.3489929 | 0.1219735 |\n", - "| 5 | Non-shuffled | Flagellin 1.0 ug/ml - DMSO 0.025% | Pyroptosis | Flagellin 1.0 ug/ml | DMSO 0.025% | 0.7013889 | 0.7706767 |\n", - "| 6 | Shuffled | Flagellin 1.0 ug/ml - DMSO 0.025% | Pyroptosis | Flagellin 1.0 ug/ml | DMSO 0.025% | 0.4410384 | 0.1403870 |\n", - "\n" - ], - "text/plain": [ - " shuffled oneb_Metadata_Treatment_Dose_Inhibitor_Dose Metadata_labels\n", - "1 Non-shuffled DMSO 0.1% - DMSO 0.025% Control \n", - "2 Shuffled DMSO 0.1% - DMSO 0.025% Control \n", - "3 Non-shuffled Flagellin 0.1 ug/ml - DMSO 0.025% Control \n", - "4 Shuffled Flagellin 0.1 ug/ml - DMSO 0.025% Control \n", - "5 Non-shuffled Flagellin 1.0 ug/ml - DMSO 0.025% Pyroptosis \n", - "6 Shuffled Flagellin 1.0 ug/ml - DMSO 0.025% Pyroptosis \n", - " inducer inhibitor morphology_ap secretome_ap\n", - "1 DMSO 0.1% DMSO 0.025% 0.6877238 0.2060009 \n", - "2 DMSO 0.1% DMSO 0.025% 0.6842913 0.1808192 \n", - "3 Flagellin 0.1 ug/ml DMSO 0.025% 0.9791667 1.0000000 \n", - "4 Flagellin 0.1 ug/ml DMSO 0.025% 0.3489929 0.1219735 \n", - "5 Flagellin 1.0 ug/ml DMSO 0.025% 0.7013889 0.7706767 \n", - "6 Flagellin 1.0 ug/ml DMSO 0.025% 0.4410384 0.1403870 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled\n", - "merged_df <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels + inducer + inhibitor, data=merged_df, FUN=mean)\n", - "head(merged_df)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 900, - "width": 900 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "width <- 15\n", - "height <- 15\n", - "options(repr.plot.width=width, repr.plot.height=height)\n", - "# scatter plot with fill being the treatment dose\n", - "scatter_by_treatment <- (\n", - " ggplot(merged_df, aes(x=morphology_ap, y=secretome_ap, col = inducer, shape=inhibitor))\n", - " + geom_point(size=3, alpha=1)\n", - " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", - " + theme_bw()\n", - " + ggtitle(\"Comparison of mAP scores\")\n", - " + ylim(0,1)\n", - " + xlim(0,1)\n", - " + figure_theme\n", - " # Change the legend title\n", - " # change the legend shape\n", - " + scale_color_manual(\n", - " name = \"Inducer\",\n", - " labels = c(\n", - " 'Media',\n", - " 'DMSO 0.1%',\n", - "\n", - " 'Flagellin 0.1 ug/ml',\n", - " 'Flagellin 1.0 ug/ml',\n", - "\n", - " 'LPS 0.01 ug/ml',\n", - " 'LPS 0.1 ug/ml',\n", - " 'LPS 1.0 ug/ml',\n", - " 'LPS 10.0 ug/ml',\n", - " 'LPS 100.0 ug/ml',\n", - "\n", - " 'LPS 1.0 ug/ml + Nigericin 1.0 uM',\n", - " 'LPS 1.0 ug/ml + Nigericin 3.0 uM',\n", - " 'LPS 1.0 ug/ml + Nigericin 10.0 uM',\n", - "\n", - " 'LPS 100.0 ug/ml + Nigericin 1.0 uM',\n", - " 'LPS 100.0 ug/ml + Nigericin 3.0 uM',\n", - " 'LPS 100.0 ug/ml + Nigericin 10.0 uM',\n", - "\n", - " 'H2O2 100.0 nM',\n", - " 'H2O2 100.0 uM',\n", - "\n", - " 'Disulfiram 0.1 uM',\n", - " 'Disulfiram 1.0 uM',\n", - " 'Disulfiram 2.5 uM',\n", - "\n", - " 'Thapsigargin 1.0 uM',\n", - " 'Thapsigargin 10.0 uM',\n", - "\n", - " 'Topotecan 5.0 nM',\n", - " 'Topotecan 10.0 nM',\n", - " 'Topotecan 20.0 nM'\n", - " ),\n", - " values = colors)\n", - " + scale_shape_manual(\n", - " name = \"Inhibitor\",\n", - " labels = c(\n", - " 'Media',\n", - " 'DMSO 0.025%',\n", - " 'DMSO 1.0%',\n", - "\n", - " 'Disulfiram 0.1 uM',\n", - " 'Disulfiram 1.0 uM',\n", - " 'Disulfiram 2.5 uM',\n", - "\n", - " 'Z-VAD-FMK 30.0 uM',\n", - " 'Z-VAD-FMK 100.0 uM'\n", - "\n", - " ),\n", - " values = shapes\n", - " )\n", - " # make the legend 1 column\n", - " + guides(color = guide_legend(ncol = 1), shape = guide_legend(ncol = 1))\n", - " + ggplot2::coord_fixed()\n", - " + facet_grid(shuffled~.)\n", - " # add y = x line\n", - " + geom_abline(intercept = 0, slope = 1, linetype = \"dashed\", color = \"black\")\n", - ")\n", - "scatter_by_treatment" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "R", - "language": "R", - "name": "ir" - }, - "language_info": { - "codemirror_mode": "r", - "file_extension": ".r", - "mimetype": "text/x-r-source", - "name": "R", - "pygments_lexer": "r", - "version": "4.2.2" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/9.mAP/run_map_analysis.sh b/9.mAP/run_map_analysis.sh index 1773aaeb9..2a88072f0 100644 --- a/9.mAP/run_map_analysis.sh +++ b/9.mAP/run_map_analysis.sh @@ -13,14 +13,18 @@ cd scripts || exit # change to the scripts directory but exit if it fails # run the .py files (the map analysis) +python 0.generate_map_scores_morphology.py --shuffle python 0.generate_map_scores_morphology.py -python 1.aggregate_map_scores_morphology.py -python 2.generate_map_scores_secretome.py -python 3.aggregate_map_scores_secretome.py -python 4.generate_map_scores_morphology_treatment.py -python 5.aggregate_map_scores_morphology_treatment.py -python 6.generate_map_scores_secretome_treatment.py -python 7.aggregate_map_scores_secretome_treatment.py +python 1.generate_map_scores_secretome.py --shuffle +python 1.generate_map_scores_secretome.py + +conda deactivate + +conda activate Interstellar_R + +Rscript 2.visualize_map_scores.r + +conda deactivate # move back to the main directory cd ../ || exit diff --git a/9.mAP/scripts/0.generate_map_scores_morphology.py b/9.mAP/scripts/0.generate_map_scores_morphology.py index fc619056f..faa3be4c1 100644 --- a/9.mAP/scripts/0.generate_map_scores_morphology.py +++ b/9.mAP/scripts/0.generate_map_scores_morphology.py @@ -4,121 +4,36 @@ # In[1]: -import itertools -import logging +import argparse import pathlib -import sys -from typing import Optional +import random import numpy as np import pandas as pd import toml -from copairs.map import run_pipeline -from pycytominer import feature_select - -# imports src -sys.path.append("../") -from src import utils - -# setting up logger -logging.basicConfig( - filename="map_analysis_testing.log", - level=logging.DEBUG, - format="%(levelname)s:%(asctime)s:%(name)s:%(message)s", -) +from copairs import map +from copairs.matching import assign_reference_index +# check if in a jupyter notebook +try: + cfg = get_ipython().config + in_notebook = True +except NameError: + in_notebook = False -# ## Helper functions -# Set of helper functions to help out throughout the notebook # In[2]: -## Helper function - - -def shuffle_meta_labels( - dataset: pd.DataFrame, target_col: str, seed: Optional[int] = 0 -) -> pd.DataFrame: - """shuffles labels or values within a single selected column - - Parameters - ---------- - dataset : pd.DataFrame - dataframe containing the dataset - - target_col : str - Column to select in order to conduct the shuffling - - seed : int - setting random seed - - Returns - ------- - pd.DataFrame - shuffled dataset - - Raises - ------ - TypeError - raised if incorrect types are provided - """ - # setting seed - np.random.seed(seed) - - # type checking - if not isinstance(target_col, str): - raise TypeError("'target_col' must be a string type") - if not isinstance(dataset, pd.DataFrame): - raise TypeError("'dataset' must be a pandas dataframe") - - # selecting column, shuffle values within column, add to dataframe - dataset[target_col] = np.random.permutation(dataset[target_col].values) - return dataset - - -def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.array: - """suffles all values within feature space - - Parameters - ---------- - feature_vals : np.array - shuffled - - seed : Optional[int] - setting random seed - - Returns - ------- - np.array - Returns shuffled values within the feature space - - Raisespairs(sameby=pos_s - TypeError - Raised if a numpy array is not provided - """ - # setting seed - np.random.seed(seed) - - # shuffle given array - if not isinstance(feature_vals, np.ndarray): - raise TypeError("'feature_vals' must be a numpy array") - if feature_vals.ndim != 2: - raise TypeError("'feature_vals' must be a 2x2 matrix") +if not in_notebook: + parser = argparse.ArgumentParser(description="Match pairs of samples") + parser.add_argument("--shuffle", action="store_true", help="Shuffle the data") - # creating a copy for feature vales to prevent overwriting of global variables - feature_vals = np.copy(feature_vals) + args = parser.parse_args() + shuffle = args.shuffle +else: + shuffle = True - # shuffling feature space - n_cols = feature_vals.shape[1] - for col_idx in range(0, n_cols): - # selecting column, shuffle, and update: - # feature_vals[:, col_idx] = np.random.permutation(feature_vals[:, col_idx]) - np.random.shuffle(feature_vals[:, col_idx]) - return feature_vals - - -# ## Setting up Paths and loading data # In[3]: @@ -133,55 +48,38 @@ def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.arra pyroptosis_ground_truth = ground_truth["Pyroptosis"]["pyroptosis_groups_list"] control_ground_truth = ground_truth["Healthy"]["healthy_groups_list"] - -# In[4]: - - -single_cell_data = pathlib.Path( - f"../../data/PBMC_preprocessed_sc_norm_aggregated.parquet" -).resolve(strict=True) -df = pd.read_parquet(single_cell_data) - - -# In[5]: - - -# out paths map_out_dir = pathlib.Path("../data/processed/mAP_scores/morphology/") map_out_dir.mkdir(exist_ok=True, parents=True) -# regular data output -# saving to csv -regular_feat_map_path = pathlib.Path(map_out_dir / "mAP_scores_regular_class.csv") -# shuffled data output -shuffled_feat_map_path = pathlib.Path(map_out_dir / "mAP_scores_shuffled_class.csv") +# In[4]: -# shuffled feature space output -shuffled_feat_space_map_path = pathlib.Path( - map_out_dir / "mAP_scores_shuffled_feature_space_class.csv" -) +agg_data = pathlib.Path( + "../../data/PBMC_preprocessed_sc_norm_aggregated.parquet" +).resolve(strict=True) +df = pd.read_parquet(agg_data) +# rename oneb_Metadata_Treatment_Dose_Inhibitor_Dose to Metadata_Treatment +df = df.rename( + columns={"oneb_Metadata_Treatment_Dose_Inhibitor_Dose": "Metadata_Treatment"} +) +df.head() -# ### Clean up data -# In[6]: +# In[5]: # add apoptosis, pyroptosis and healthy columns to dataframe df["Apoptosis"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in apoptosis_ground_truth, + lambda row: row["Metadata_Treatment"] in apoptosis_ground_truth, axis=1, ) df["Pyroptosis"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in pyroptosis_ground_truth, + lambda row: row["Metadata_Treatment"] in pyroptosis_ground_truth, axis=1, ) df["Control"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in control_ground_truth, + lambda row: row["Metadata_Treatment"] in control_ground_truth, axis=1, ) @@ -194,188 +92,69 @@ def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.arra else "Control", axis=1, ) +metadata_labels = df.pop("Metadata_labels") +df.insert(1, "Metadata_labels", metadata_labels) # # drop apoptosis, pyroptosis, and healthy columns df.drop(columns=["Apoptosis", "Pyroptosis", "Control"], inplace=True) -df.drop(columns=["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"], inplace=True) - - -# In[7]: -# output directories -map_out_dir = pathlib.Path("../data/processed/mAP_scores/") -map_out_dir.mkdir(parents=True, exist_ok=True) +# In[6]: -# ### mAP Pipeline Parameters +if shuffle: + random.seed(0) + # permutate the data + for col in df.columns: + df[col] = np.random.permutation(df[col]) -# The null size needs to be determined for the mAP pipeline. This is the size of the null class that is used to determine the mAP score. -# In[8]: +# In[7]: -tmp = ( - df.groupby(["Metadata_labels"]) - .count() - .reset_index()[["Metadata_Well", "Metadata_labels"]] +reference_col = "Metadata_reference_index" +df_activity = assign_reference_index( + df, + "Metadata_Treatment == 'DMSO_0.100_%_DMSO_0.025_%'", + reference_col=reference_col, + default_value=-1, ) -# get the Pyroptosis number of Metadata_Well -Pyroptosis_count = tmp[tmp["Metadata_labels"] == "Pyroptosis"]["Metadata_Well"].values[ - 0 -] -Pyroptosis_count +df_activity.head() -# In[9]: - +# In[8]: -pos_sameby = [ - "Metadata_labels", -] -pos_diffby = ["Metadata_Well"] +pos_sameby = ["Metadata_Treatment", "Metadata_labels", reference_col] +pos_diffby = [] neg_sameby = [] -neg_diffby = ["Metadata_labels"] - -null_size = Pyroptosis_count -batch_size = 1 - - -# ### mAP analysis for non-shuffled data - -# In[10]: - +neg_diffby = ["Metadata_Treatment", reference_col] +metadata = df_activity.filter(regex="Metadata") +profiles = df_activity.filter(regex="^(?!Metadata)").values -# generate the permutations of cell death labels via itertools -pos_samby_permutations = list(itertools.combinations(df["Metadata_labels"].unique(), 2)) - - -# In[11]: - - -results_df = pd.DataFrame( - columns=[ - "Metadata_Well", - "Metadata_labels", - "average_precision", - "p_value", - "n_pos_pairs", - "n_total_pairs", - "shuffled", - "comparison", - ] +activity_ap = map.average_precision( + metadata, profiles, pos_sameby, pos_diffby, neg_sameby, neg_diffby ) +activity_ap = activity_ap.query("Metadata_Treatment != 'DMSO_0.100_%_DMSO_0.025_%'") +activity_ap.head() -# In[12]: - - -for i in pos_samby_permutations: - tmp = df.copy() - # get only the rows with the current permutation - tmp = tmp[tmp["Metadata_labels"].isin(i)] - # This will generated 100 values [0..100] as seed values - # This will occur per phenotype - - # spliting metadata and raw feature values - logging.info("splitting data set into metadata and raw feature values") - df_meta, df_feats = utils.split_data(tmp) - df_feats = np.array(df_feats) - - # execute pipeline on negative control with training dataset with cp features - try: - # execute pipeline on negative control with trianing dataset with cp features - - logging.info(f"Running pipeline on CP features using phenotype") - result = run_pipeline( - meta=df_meta, - feats=df_feats, - pos_sameby=pos_sameby, - pos_diffby=pos_diffby, - neg_sameby=neg_sameby, - neg_diffby=neg_diffby, - batch_size=batch_size, - null_size=null_size, - ) - - # adding columns - result["shuffled"] = "non-shuffled" - result["comparison"] = "_vs_".join(i) - - except ZeroDivisionError as e: - logging.warning(f"{e} captured on phenotye:. Skipping") - - # concatenating all datasets - results_df = pd.concat([results_df, result], ignore_index=True) -results_df.to_csv(regular_feat_map_path, index=False) +# In[9]: -# ### mAP analysis for shuffled data (Feature space) -# In[13]: +activity_map = map.mean_average_precision( + activity_ap, pos_sameby, null_size=1000000, threshold=0.05, seed=0 +) +activity_map["-log10(p-value)"] = -activity_map["corrected_p_value"].apply(np.log10) +# flatten the multi-index columns to make it easier to work with +activity_map.reset_index(inplace=True) +activity_map.head() -results_df = pd.DataFrame( - columns=[ - "Metadata_Well", - "Metadata_labels", - "average_precision", - "p_value", - "n_pos_pairs", - "n_total_pairs", - "shuffled", - "comparison", - ] -) +# In[10]: -# In[14]: - - -for i in pos_samby_permutations: - tmp = df.copy() - # get only the rows with the current permutation - tmp = tmp[tmp["Metadata_labels"].isin(i)] - # This will generated 100 values [0..100] as seed values - seed = np.random.randint(0, 100) - - # split the shuffled dataset - # spliting metadata and raw feature values - logging.info("splitting shuffled data set into metadata and raw feature values") - ( - df_meta, - df_feats, - ) = utils.split_data(tmp) - - df_feats = np.array(df_feats) - - # shuffling the features, this will overwrite the generated feature space from above with the shuffled one - df_feats = shuffle_features(feature_vals=df_feats, seed=seed) - - try: - # execute pipeline on negative control with trianing dataset with cp features - logging.info( - f"Running pipeline on CP features using phenotype, feature space is shuffled" - ) - shuffled_feat_map = run_pipeline( - meta=df_meta, - feats=df_feats, - pos_sameby=pos_sameby, - pos_diffby=pos_diffby, - neg_sameby=neg_sameby, - neg_diffby=neg_diffby, - batch_size=batch_size, - null_size=null_size, - ) - - # adding shuffle label column - shuffled_feat_map["shuffled"] = "shuffled" - shuffled_feat_map["comparison"] = "_vs_".join(i) - - except ZeroDivisionError as e: - logging.warning(f"{e} captured on phenotype: Skipping") - - # concatenating all datasets - results_df = pd.concat([results_df, shuffled_feat_map], ignore_index=True) - # saving to csv -results_df.to_csv(shuffled_feat_space_map_path, index=False) +if shuffle: + activity_map.to_parquet(map_out_dir / "activity_map_shuffled.parquet") +else: + activity_map.to_parquet(map_out_dir / "activity_map.parquet") diff --git a/9.mAP/scripts/1.aggregate_map_scores_morphology.py b/9.mAP/scripts/1.aggregate_map_scores_morphology.py deleted file mode 100644 index 2b13a6086..000000000 --- a/9.mAP/scripts/1.aggregate_map_scores_morphology.py +++ /dev/null @@ -1,93 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -import pathlib -import warnings - -import numpy as np -import pandas as pd -import plotly.express as px -from copairs.map import aggregate - -warnings.filterwarnings("ignore") - - -# In[2]: - - -# Directories -processed_data_dir = pathlib.Path("../data/processed/") -sc_ap_scores_dir = (processed_data_dir / "mAP_scores/morphology").resolve() -agg_sc_ap_scores_dir = (processed_data_dir / "aggregate_mAPs/morphology").resolve() -agg_sc_ap_scores_dir.mkdir(parents=True, exist_ok=True) - - -# ## Preparing the dataset -# - -# In[3]: - - -all_files = list(sc_ap_scores_dir.glob("*.csv")) -# get the files that contain the string class -class_files = [file for file in all_files if "class" in file.stem] -mAPs = [] -for file in class_files: - df = pd.read_csv(file) - df["file"] = file.stem - mAPs.append(df) -# single-cell mAP scores -mAPs = pd.concat(mAPs) -mAPs.head() -mAPs["comparison"].unique() - - -# In[4]: - - -# grabbing all cp features (regular, feature shuffled and labeled shuffled) -reg_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "non-shuffled"] -shuffled_feat_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "features_shuffled"] - - -# In[5]: - - -# calculating sampling error -# grouping dataframe based on phenotype levels, feature and feature types -df_group = mAPs.groupby(by=["Metadata_labels", "shuffled", "comparison"]) -df_group -sampling_error_df = [] -for name, df in df_group: - pheno, shuffled_type, comparison = name - - # caclulating sampling error - avg_percision = df["average_precision"].values - sampling_error = np.std(avg_percision) / np.sqrt(len(avg_percision)) - - sampling_error_df.append([pheno, shuffled_type, sampling_error, comparison]) -cols = ["Metadata_labels", "shuffled", "sampling_error", "comparison"] -sampling_error_df = pd.DataFrame(sampling_error_df, columns=cols) - - -sampling_error_df.head() - - -# In[6]: - - -# Generating aggregate scores with a threshold p-value of 0.05 -mAP_dfs = [] -for name, df in tuple(mAPs.groupby(by=["Metadata_labels", "shuffled", "comparison"])): - agg_df = aggregate(df, sameby=["Metadata_labels"], threshold=0.05) - agg_df["Metadata_labels"] = name[0] - agg_df["shuffled"] = name[1] - agg_df["comparison"] = name[2] - mAP_dfs.append(agg_df) - -mAP_dfs = pd.concat(mAP_dfs) -mAP_dfs.to_csv(agg_sc_ap_scores_dir / "mAP_scores_class.csv", index=False) -mAP_dfs.head() diff --git a/9.mAP/scripts/1.generate_map_scores_secretome.py b/9.mAP/scripts/1.generate_map_scores_secretome.py new file mode 100644 index 000000000..2a6253d25 --- /dev/null +++ b/9.mAP/scripts/1.generate_map_scores_secretome.py @@ -0,0 +1,161 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[1]: + + +import argparse +import pathlib +import random + +import numpy as np +import pandas as pd +import toml +from copairs import map +from copairs.matching import assign_reference_index + +# check if in a jupyter notebook +try: + cfg = get_ipython().config + in_notebook = True +except NameError: + in_notebook = False + + +# In[2]: + + +if not in_notebook: + parser = argparse.ArgumentParser(description="Match pairs of samples") + parser.add_argument("--shuffle", action="store_true", help="Shuffle the data") + + args = parser.parse_args() + shuffle = args.shuffle +else: + shuffle = True + + +# In[3]: + + +# load in the treatment groups +ground_truth = pathlib.Path( + "../../4.sc_Morphology_Neural_Network_MLP_Model/MLP_utils/ground_truth.toml" +).resolve(strict=True) +# load in the ground truth +ground_truth = toml.load(ground_truth) +apoptosis_ground_truth = ground_truth["Apoptosis"]["apoptosis_groups_list"] +pyroptosis_ground_truth = ground_truth["Pyroptosis"]["pyroptosis_groups_list"] +control_ground_truth = ground_truth["Healthy"]["healthy_groups_list"] + +map_out_dir = pathlib.Path("../data/processed/mAP_scores/secretome/") +map_out_dir.mkdir(exist_ok=True, parents=True) + + +# In[4]: + + +agg_data = pathlib.Path( + "../../data/PBMC_preprocessed_sc_norm_aggregated_nomic.parquet" +).resolve(strict=True) +df = pd.read_parquet(agg_data) +# rename oneb_Metadata_Treatment_Dose_Inhibitor_Dose to Metadata_Treatment +df = df.rename( + columns={"oneb_Metadata_Treatment_Dose_Inhibitor_Dose": "Metadata_Treatment"} +) +df = df.filter(regex="Metadata|NSU") +df.head() + + +# In[5]: + + +# add apoptosis, pyroptosis and healthy columns to dataframe +df["Apoptosis"] = df.apply( + lambda row: row["Metadata_Treatment"] in apoptosis_ground_truth, + axis=1, +) +df["Pyroptosis"] = df.apply( + lambda row: row["Metadata_Treatment"] in pyroptosis_ground_truth, + axis=1, +) +df["Control"] = df.apply( + lambda row: row["Metadata_Treatment"] in control_ground_truth, + axis=1, +) + +# merge apoptosis, pyroptosis, and healthy columns into one column +df["Metadata_labels"] = df.apply( + lambda row: "Apoptosis" + if row["Apoptosis"] + else "Pyroptosis" + if row["Pyroptosis"] + else "Control", + axis=1, +) +metadata_labels = df.pop("Metadata_labels") +df.insert(1, "Metadata_labels", metadata_labels) +# # drop apoptosis, pyroptosis, and healthy columns +df.drop(columns=["Apoptosis", "Pyroptosis", "Control"], inplace=True) + + +# In[6]: + + +if shuffle: + random.seed(0) + # permutate the data + for col in df.columns: + df[col] = np.random.permutation(df[col]) + + +# In[7]: + + +reference_col = "Metadata_reference_index" +df_activity = assign_reference_index( + df, + "Metadata_Treatment == 'DMSO_0.100_%_DMSO_0.025_%'", + reference_col=reference_col, + default_value=-1, +) +df_activity.head() + + +# In[8]: + + +pos_sameby = ["Metadata_Treatment", "Metadata_labels", reference_col] +pos_diffby = [] +neg_sameby = [] +neg_diffby = ["Metadata_Treatment", reference_col] +metadata = df_activity.filter(regex="Metadata") +profiles = df_activity.filter(regex="^(?!Metadata)").values + +activity_ap = map.average_precision( + metadata, profiles, pos_sameby, pos_diffby, neg_sameby, neg_diffby +) + +activity_ap = activity_ap.query("Metadata_Treatment != 'DMSO_0.100_%_DMSO_0.025_%'") +activity_ap.head() + + +# In[9]: + + +activity_map = map.mean_average_precision( + activity_ap, pos_sameby, null_size=1000000, threshold=0.05, seed=0 +) +activity_map["-log10(p-value)"] = -activity_map["corrected_p_value"].apply(np.log10) +# flatten the multi-index columns to make it easier to work with +activity_map.reset_index(inplace=True) +activity_map.head() + + +# In[10]: + + +if shuffle: + activity_map.to_parquet(map_out_dir / "activity_map_shuffled.parquet") +else: + activity_map.to_parquet(map_out_dir / "activity_map.parquet") diff --git a/9.mAP/scripts/2.generate_map_scores_secretome.py b/9.mAP/scripts/2.generate_map_scores_secretome.py deleted file mode 100644 index 182c19e5f..000000000 --- a/9.mAP/scripts/2.generate_map_scores_secretome.py +++ /dev/null @@ -1,400 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -import itertools -import logging -import pathlib -import sys -from typing import Optional - -import numpy as np -import pandas as pd -import toml -from copairs.map import run_pipeline -from pycytominer import feature_select - -# imports src -sys.path.append("../") -from src import utils - -# setting up logger -logging.basicConfig( - filename="map_analysis_testing.log", - level=logging.DEBUG, - format="%(levelname)s:%(asctime)s:%(name)s:%(message)s", -) - - -# ## Helper functions -# Set of helper functions to help out throughout the notebook - -# In[2]: - - -## Helper function - - -def shuffle_meta_labels( - dataset: pd.DataFrame, target_col: str, seed: Optional[int] = 0 -) -> pd.DataFrame: - """shuffles labels or values within a single selected column - - Parameters - ---------- - dataset : pd.DataFrame - dataframe containing the dataset - - target_col : str - Column to select in order to conduct the shuffling - - seed : int - setting random seed - - Returns - ------- - pd.DataFrame - shuffled dataset - - Raises - ------ - TypeError - raised if incorrect types are provided - """ - # setting seed - np.random.seed(seed) - - # type checking - if not isinstance(target_col, str): - raise TypeError("'target_col' must be a string type") - if not isinstance(dataset, pd.DataFrame): - raise TypeError("'dataset' must be a pandas dataframe") - - # selecting column, shuffle values within column, add to dataframe - dataset[target_col] = np.random.permutation(dataset[target_col].values) - return dataset - - -def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.array: - """suffles all values within feature space - - Parameters - ---------- - feature_vals : np.array - shuffled - - seed : Optional[int] - setting random seed - - Returns - ------- - np.array - Returns shuffled values within the feature space - - Raises - ------ - TypeError - Raised if a numpy array is not provided - """ - # setting seed - np.random.seed(seed) - - # shuffle given array - if not isinstance(feature_vals, np.ndarray): - raise TypeError("'feature_vals' must be a numpy array") - if feature_vals.ndim != 2: - raise TypeError("'feature_vals' must be a 2x2 matrix") - - # creating a copy for feature vales to prevent overwriting of global variables - feature_vals = np.copy(feature_vals) - - # shuffling feature space - n_cols = feature_vals.shape[1] - for col_idx in range(0, n_cols): - # selecting column, shuffle, and update: - feature_vals[:, col_idx] = np.random.permutation(feature_vals[:, col_idx]) - - return feature_vals - - -# ## Setting up Paths and loading data - -# In[3]: - - -# load in the treatment groups -ground_truth = pathlib.Path( - "../../4.sc_Morphology_Neural_Network_MLP_Model/MLP_utils/ground_truth.toml" -).resolve(strict=True) -# load in the ground truth -ground_truth = toml.load(ground_truth) -apoptosis_ground_truth = ground_truth["Apoptosis"]["apoptosis_groups_list"] -pyroptosis_ground_truth = ground_truth["Pyroptosis"]["pyroptosis_groups_list"] -control_ground_truth = ground_truth["Healthy"]["healthy_groups_list"] - - -# In[4]: - - -single_cell_data = pathlib.Path( - f"../../data/PBMC_preprocessed_sc_norm_aggregated_nomic.parquet" -).resolve(strict=True) -df = pd.read_parquet(single_cell_data) - - -# In[5]: - - -# out paths -map_out_dir = pathlib.Path("../data/processed/mAP_scores/secretome/") -map_out_dir.mkdir(exist_ok=True, parents=True) - -# regular data output -# saving to csv -regular_feat_map_path = pathlib.Path(map_out_dir / "mAP_scores_regular_class.csv") - -# shuffled data output -shuffled_feat_map_path = pathlib.Path(map_out_dir / "mAP_scores_shuffled_class.csv") - -# shuffled feature space output -shuffled_feat_space_map_path = pathlib.Path( - map_out_dir / "mAP_scores_shuffled_feature_space_class.csv" -) - - -# ### Clean up data - -# In[6]: - - -# add apoptosis, pyroptosis and healthy columns to dataframe -df["Apoptosis"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in apoptosis_ground_truth, - axis=1, -) -df["Pyroptosis"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in pyroptosis_ground_truth, - axis=1, -) -df["Control"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in control_ground_truth, - axis=1, -) - -# merge apoptosis, pyroptosis, and healthy columns into one column -df["Metadata_labels"] = df.apply( - lambda row: "Apoptosis" - if row["Apoptosis"] - else "Pyroptosis" - if row["Pyroptosis"] - else "Control", - axis=1, -) -# # drop apoptosis, pyroptosis, and healthy columns -df.drop(columns=["Apoptosis", "Pyroptosis", "Control"], inplace=True) -df.drop(columns=["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"], inplace=True) - - -# In[7]: - - -# keep columns that contain Metdata and ['NSU'] -df = df.filter(regex="Metadata|NSU") -df.head() - - -# In[8]: - - -# output directories -map_out_dir = pathlib.Path("../data/processed/mAP_scores/") -map_out_dir.mkdir(parents=True, exist_ok=True) - - -# ### mAP Pipeline Parameters - -# The null size needs to be determined for the mAP pipeline. This is the size of the null class that is used to determine the mAP score. - -# In[9]: - - -tmp = ( - df.groupby(["Metadata_labels"]) - .count() - .reset_index()[["Metadata_Well", "Metadata_labels"]] -) -# get the Pyroptosis number of Metadata_Well -Pyroptosis_count = tmp[tmp["Metadata_labels"] == "Pyroptosis"]["Metadata_Well"].values[ - 0 -] -Pyroptosis_count - - -# In[10]: - - -pos_sameby = [ - "Metadata_labels", -] -pos_diffby = ["Metadata_Well"] - -neg_sameby = [] -neg_diffby = ["Metadata_labels"] - -null_size = Pyroptosis_count -batch_size = 1 - -# number of resampling -n_resamples = 10 - - -# ### mAP analysis for non-shuffled data - -# In[11]: - - -# generate the permutations of cell death labels via itertools -pos_samby_permutations = list(itertools.combinations(df["Metadata_labels"].unique(), 2)) - - -# In[13]: - - -results_df = pd.DataFrame( - columns=[ - "Metadata_Well", - "Metadata_labels", - "average_precision", - "p_value", - "n_pos_pairs", - "n_total_pairs", - "shuffled", - "comparison", - ] -) - - -# In[14]: - - -for i in pos_samby_permutations: - # print(i) - tmp = df.copy() - # get only the rows with the current permutation - tmp = tmp[tmp["Metadata_labels"].isin(i)] - # This will generated 100 values [0..100] as seed values - # This will occur per phenotype - - # spliting metadata and raw feature values - logging.info("splitting data set into metadata and raw feature values") - df_meta, df_feats = utils.split_data(tmp) - df_feats = np.array(df_feats) - - # execute pipeline on negative control with training dataset with cp features - try: - # execute pipeline on negative control with trianing dataset with cp features - - logging.info(f"Running pipeline on CP features using phenotype") - result = run_pipeline( - meta=df_meta, - feats=df_feats, - pos_sameby=pos_sameby, - pos_diffby=pos_diffby, - neg_sameby=neg_sameby, - neg_diffby=neg_diffby, - batch_size=batch_size, - null_size=null_size, - ) - - # adding columns - result["shuffled"] = "non-shuffled" - result["comparison"] = "_vs_".join(i) - - except ZeroDivisionError as e: - logging.warning(f"{e} captured on phenotye:. Skipping") - - # concatenating all datasets - results_df = pd.concat([results_df, result], ignore_index=True) -# concatenating all datasets -results_df.to_csv(regular_feat_map_path, index=False) -result.head() - - -# ### mAP analysis for shuffled data (Feature space) - -# In[15]: - - -results_df = pd.DataFrame( - columns=[ - "Metadata_Well", - "Metadata_labels", - "average_precision", - "p_value", - "n_pos_pairs", - "n_total_pairs", - "shuffled", - "comparison", - ] -) - - -# In[16]: - - -for i in pos_samby_permutations: - # print(i) - tmp = df.copy() - # get only the rows with the current permutation - tmp = tmp[tmp["Metadata_labels"].isin(i)] - # This will generated 100 values [0..100] as seed values - seed = np.random.randint(0, 100) - - # split the shuffled dataset - # spliting metadata and raw feature values - logging.info("splitting shuffled data set into metadata and raw feature values") - ( - df_meta, - df_feats, - ) = utils.split_data(tmp) - - df_feats = np.array(df_feats) - - # shuffling the features, this will overwrite the generated feature space from above with the shuffled one - df_feats = shuffle_features(feature_vals=df_feats, seed=seed) - - try: - # execute pipeline on negative control with trianing dataset with cp features - logging.info( - f"Running pipeline on CP features using phenotype, feature space is shuffled" - ) - shuffled_feat_map = run_pipeline( - meta=df_meta, - feats=df_feats, - pos_sameby=pos_sameby, - pos_diffby=pos_diffby, - neg_sameby=neg_sameby, - neg_diffby=neg_diffby, - batch_size=batch_size, - null_size=null_size, - ) - - # adding shuffle label column - shuffled_feat_map["shuffled"] = "shuffled" - shuffled_feat_map["comparison"] = "_vs_".join(i) - - except ZeroDivisionError as e: - logging.warning(f"{e} captured on phenotype: Skipping") - - # concatenating all datasets - results_df = pd.concat([results_df, shuffled_feat_map], ignore_index=True) - # saving to csv - -# saving to csv -results_df.to_csv(shuffled_feat_space_map_path, index=False) -results_df.head() diff --git a/9.mAP/scripts/2.visualize_map_scores.r b/9.mAP/scripts/2.visualize_map_scores.r new file mode 100644 index 000000000..604c2bcac --- /dev/null +++ b/9.mAP/scripts/2.visualize_map_scores.r @@ -0,0 +1,340 @@ +suppressPackageStartupMessages(suppressWarnings(library(ggplot2))) +suppressPackageStartupMessages(suppressWarnings(library(RColorBrewer))) +suppressPackageStartupMessages(suppressWarnings(library(dplyr))) +suppressPackageStartupMessages(suppressWarnings(library(tidyr))) +suppressPackageStartupMessages(suppressWarnings(library(arrow))) +source("../../figures/utils/figure_themes.r") + +# set path to the data morphology + +morphology_path <- file.path("..","data","processed","mAP_scores","morphology","activity_map.parquet") +shuffled_morphology_path <- file.path("..","data","processed","mAP_scores","morphology","activity_map_shuffled.parquet") +# set path to the secretome data + +secretome_path <- file.path("..","data","processed","mAP_scores","secretome","activity_map.parquet") +shuffled_secretome_path <- file.path("..","data","processed","mAP_scores","secretome","activity_map_shuffled.parquet") + +df_morphology <- arrow::read_parquet(morphology_path) %>% + dplyr::mutate(shuffled = "Non-shuffled") %>% + dplyr::mutate(data_type = "Morphology") %>% + # rename the mean_average_precision column to specifcy morphology + # drop unnecessary columns + dplyr::select(-c("Metadata_reference_index", "indices", "p_value", "corrected_p_value", "below_p", "below_corrected_p","-log10(p-value)")) + +df_shuffled_morphology <- arrow::read_parquet(shuffled_morphology_path) %>% + dplyr::mutate(shuffled = "Shuffled") %>% + dplyr::mutate(data_type = "Morphology") %>% + # rename the mean_average_precision column to specifcy morphology + dplyr::select(-c("Metadata_reference_index", "indices", "p_value", "corrected_p_value", "below_p", "below_corrected_p","-log10(p-value)")) + + +df_secretome <- arrow::read_parquet(secretome_path) %>% + dplyr::mutate(shuffled = "Non-shuffled") %>% + dplyr::mutate(data_type = "Secretome") %>% + # rename the mean_average_precision column to specifcy secretome + dplyr::select(-c("Metadata_reference_index", "indices", "p_value", "corrected_p_value", "below_p", "below_corrected_p","-log10(p-value)")) + + +df_shuffled_secretome <- arrow::read_parquet(shuffled_secretome_path) %>% + dplyr::mutate(shuffled = "Shuffled") %>% + dplyr::mutate(data_type = "Secretome") %>% + # rename the mean_average_precision column to specifcy secretome + dplyr::select(-c("Metadata_reference_index", "indices", "p_value", "corrected_p_value", "below_p", "below_corrected_p","-log10(p-value)")) + +df <- dplyr::bind_rows(df_morphology, df_shuffled_morphology, df_secretome, df_shuffled_secretome) +head(df) + +# split out the morphology and secretome data +morphology_data <- df %>% dplyr::filter(data_type == "Morphology") +secretome_data <- df %>% dplyr::filter(data_type == "Secretome") +# rename the mean_average_precision column to specifcy morphology +morphology_data <- morphology_data %>% dplyr::rename(mAP_moprhology = mean_average_precision) +secretome_data <- secretome_data %>% dplyr::rename(mAP_secretome = mean_average_precision) +# drop the data_type column +morphology_data <- morphology_data %>% dplyr::select(-data_type) +secretome_data <- secretome_data %>% dplyr::select(-data_type) +# merge the data together to plot +df <- merge(morphology_data, secretome_data,by = c("Metadata_Treatment", "Metadata_labels", "shuffled")) + +levels_list <- c( + 'Media', + 'DMSO_0.100_%_DMSO_0.025_%', + 'DMSO_0.100_%_DMSO_1.000_%', + 'DMSO_0.100_%_Z-VAD-FMK_30.000_uM', + 'DMSO_0.100_%_Z-VAD-FMK_100.000_uM', + + 'Disulfiram_0.100_uM_DMSO_0.025_%', + 'Disulfiram_1.000_uM_DMSO_0.025_%', + 'Disulfiram_2.500_uM_DMSO_0.025_%', + + 'Flagellin_0.100_ug_per_ml_DMSO_0.025_%', + 'Flagellin_1.000_ug_per_ml_DMSO_0.025_%', + 'Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM', + + 'LPS_0.010_ug_per_ml_DMSO_0.025_%', + 'LPS_0.100_ug_per_ml_DMSO_0.025_%', + 'LPS_1.000_ug_per_ml_DMSO_0.025_%', + + 'LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%', + 'LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%', + 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%', + 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM', + 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM', + + 'LPS_10.000_ug_per_ml_DMSO_0.025_%', + 'LPS_10.000_ug_per_ml_Disulfiram_0.100_uM', + 'LPS_10.000_ug_per_ml_Disulfiram_1.000_uM', + 'LPS_10.000_ug_per_ml_Disulfiram_2.500_uM', + 'LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM', + + 'LPS_100.000_ug_per_ml_DMSO_0.025_%', + 'LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%', + 'LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%', + 'LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%', + + 'H2O2_100.000_nM_DMSO_0.025_%', + 'H2O2_100.000_uM_DMSO_0.025_%', + 'H2O2_100.000_uM_Disulfiram_1.000_uM', + 'H2O2_100.000_uM_Z-VAD-FMK_100.000_uM', + 'Thapsigargin_1.000_uM_DMSO_0.025_%', + 'Thapsigargin_10.000_uM_DMSO_0.025_%', + + 'Topotecan_5.000_nM_DMSO_0.025_%', + 'Topotecan_10.000_nM_DMSO_0.025_%', + 'Topotecan_20.000_nM_DMSO_0.025_%' +) + +df$Metadata_labels <- factor(df$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) +df$Metadata_Treatment <- factor(df$Metadata_Treatment, levels =levels_list) + +# scatter plot +scatter_compare_treatment <- ( + ggplot(df, aes(x=mAP_moprhology, y=mAP_secretome, col = Metadata_labels, shape=shuffled)) + + geom_point(size=3, alpha=0.5) + + labs(x="Morphology mAP score", y="Secretome mAP score") + + theme_bw() + + ggtitle("Comparison of mAP scores") + + ylim(0,1) + + xlim(0,1) + # Change the legend title + # change the legend shape + + scale_shape_manual( + name="Shuffle type", + labels=c( + "Non-shuffled", + "Shuffled features", + "Shuffled phenotypes" + ), + values=c(19, 17, 15) + ) + + scale_color_manual( + name="Class", + labels=c( + "Control", + "Apoptosis", + "Pyroptosis" + ), + values=c( + brewer.pal(3, "Dark2")[2], + brewer.pal(3, "Dark2")[1], + brewer.pal(3, "Dark2")[3] + ) +) + + figure_theme + # add y = x line + + geom_abline(intercept = 0, slope = 1, linetype="dashed", color = "black") +) +scatter_compare_treatment + +df <- df %>% + mutate(Metadata_Treatment = case_when( + Metadata_Treatment =='DMSO_0.100_%_DMSO_0.025_%' ~ "DMSO 0.1% - DMSO 0.025%", + Metadata_Treatment =='DMSO_0.100_%_DMSO_1.000_%' ~ "DMSO 0.1% - DMSO 1.0%", + Metadata_Treatment =='DMSO_0.100_%_Z-VAD-FMK_100.000_uM' ~ "DMSO 0.1% - Z-VAD-FMK 100.0 uM", + Metadata_Treatment =='DMSO_0.100_%_Z-VAD-FMK_30.000_uM' ~ "DMSO 0.1% - Z-VAD-FMK 30.0 uM", + Metadata_Treatment =='Flagellin_1.000_ug_per_ml_DMSO_0.025_%' ~ "Flagellin 1.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM' ~ "Flagellin 1.0 ug/ml - Disulfiram 1.0 uM", + Metadata_Treatment =='LPS_0.010_ug_per_ml_DMSO_0.025_%' ~ "LPS 0.01 ug/ml - DMSO 0.025%", + Metadata_Treatment =='LPS_0.100_ug_per_ml_DMSO_0.025_%' ~ "LPS 0.1 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Flagellin_0.100_ug_per_ml_DMSO_0.0_%' ~ "Flagellin 0.1 ug/ml - DMSO 0.0%", + Metadata_Treatment =='Flagellin_0.100_ug_per_ml_DMSO_0.025_%' ~ "Flagellin 0.1 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Disulfiram_0.100_uM_DMSO_0.025_%' ~ "Disulfiram 0.1 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - Disulfiram 1.0 uM", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - Z-VAD-FMK 100.0 uM", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_1.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 1.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Flagellin_1.000_ug_per_ml_DMSO_0.0_%' ~ "Flagellin 1.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Disulfiram_1.000_uM_DMSO_0.025_%' ~ "Disulfiram 1.0 uM - DMSO 0.025%", + Metadata_Treatment =='Thapsigargin_1.000_uM_DMSO_0.025_%' ~ "Thapsigargin 1.0 uM - DMSO 0.025%", + Metadata_Treatment =='Topotecan_10.000_nM_DMSO_0.025_%' ~ "Topotecan 10.0 nM - DMSO 0.025%", + Metadata_Treatment =='LPS_10.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 10.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_0.100_uM' ~ "LPS 10.0 ug/ml - Disulfiram 0.1 uM", + Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_1.000_uM' ~ "LPS 10.0 ug/ml - Disulfiram 1.0 uM", + Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_2.500_uM' ~ "LPS 10.0 ug/ml - Disulfiram 2.5 uM", + Metadata_Treatment =='LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM' ~ "LPS 10.0 ug/ml - Z-VAD-FMK 100.0 uM", + Metadata_Treatment =='Thapsigargin_10.000_uM_DMSO_0.025_%' ~ "Thapsigargin 10.0 uM - DMSO 0.025%", + Metadata_Treatment =='H2O2_100.000_nM_DMSO_0.025_%' ~ "H2O2 100.0 nM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_100.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 100.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='H2O2_100.000_uM_DMSO_0.025_%' ~ "H2O2 100.0 uM - DMSO 0.025%", + Metadata_Treatment =='H2O2_100.000_uM_Disulfiram_1.000_uM' ~ "H2O2 100.0 uM - Disulfiram 1.0 uM", + Metadata_Treatment =='H2O2_100.000_uM_Z-VAD-FMK_100.000_uM' ~ "H2O2 100.0 uM - Z-VAD-FMK 100.0 uM", + Metadata_Treatment =='Disulfiram_2.500_uM_DMSO_0.025_%' ~ "Disulfiram 2.5 uM - DMSO 0.025%", + Metadata_Treatment =='Topotecan_20.000_nM_DMSO_0.025_%' ~ "Topotecan 20.0 nM - DMSO 0.025%", + Metadata_Treatment =='Topotecan_5.000_nM_DMSO_0.025_%' ~ "Topotecan 5.0 nM - DMSO 0.025%", + Metadata_Treatment =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ "Media ctr 0.0 0", + Metadata_Treatment =='media_ctr_0.0_0_Media_0.0_0' ~ "Media ctr 0.0 0" + )) + # replace Media ctr 0.0 0 with Media +df$Metadata_Treatment <- gsub("Media ctr 0.0 0", "Media", df$Metadata_Treatment) + +# split the Metadata_Treatment into two columns by the " - " delimiter +df <- df %>% + separate(Metadata_Treatment, c("inducer", "inhibitor"), sep = " - ", remove = FALSE) + +# replace the inhibitor NA with Media +df$inhibitor <- ifelse(is.na(df$inhibitor), "Media", df$inhibitor) + +# make the group_treatment column a factor +df$inducer <- factor( + df$inducer, + levels = c( + 'Media', + 'DMSO 0.1%', + + 'Flagellin 0.1 ug/ml', + 'Flagellin 1.0 ug/ml', + + 'LPS 0.01 ug/ml', + 'LPS 0.1 ug/ml', + 'LPS 1.0 ug/ml', + 'LPS 10.0 ug/ml', + 'LPS 100.0 ug/ml', + + 'LPS 1.0 ug/ml + Nigericin 1.0 uM', + 'LPS 1.0 ug/ml + Nigericin 3.0 uM', + 'LPS 1.0 ug/ml + Nigericin 10.0 uM', + + 'LPS 100.0 ug/ml + Nigericin 1.0 uM', + 'LPS 100.0 ug/ml + Nigericin 3.0 uM', + 'LPS 100.0 ug/ml + Nigericin 10.0 uM', + + 'H2O2 100.0 nM', + 'H2O2 100.0 uM', + + 'Disulfiram 0.1 uM', + 'Disulfiram 1.0 uM', + 'Disulfiram 2.5 uM', + + 'Thapsigargin 1.0 uM', + 'Thapsigargin 10.0 uM', + + 'Topotecan 5.0 nM', + 'Topotecan 10.0 nM', + 'Topotecan 20.0 nM' + ) +) + +# make the group_treatment column a factor +df$inhibitor <- factor( + df$inhibitor, + levels = c( + 'Media', + 'DMSO 0.025%', + 'DMSO 1.0%', + + 'Disulfiram 0.1 uM', + 'Disulfiram 1.0 uM', + 'Disulfiram 2.5 uM', + + 'Z-VAD-FMK 30.0 uM', + 'Z-VAD-FMK 100.0 uM' + ) +) +head(df) + +# save the df to as parquet for plotting later on +arrow::write_parquet(df, file.path("..","data","processed","mAP_scores","morphology_secretome_comparison.parquet")) + +width <- 15 +height <- 15 +options(repr.plot.width=width, repr.plot.height=height) +# scatter plot with fill being the treatment dose +scatter_by_treatment <- ( + ggplot(df, aes(x=mAP_moprhology, y=mAP_secretome, col = inducer, shape=inhibitor)) + + geom_point(size=3, alpha=1) + + labs(x="Morphology mAP score", y="Secretome mAP score") + + theme_bw() + + ggtitle("Comparison of mAP scores") + + ylim(0,1) + + xlim(0,1) + + figure_theme + # Change the legend title + # change the legend shape + + scale_color_manual( + name = "Inducer", + labels = c( + 'Media', + 'DMSO 0.1%', + + 'Flagellin 0.1 ug/ml', + 'Flagellin 1.0 ug/ml', + + 'LPS 0.01 ug/ml', + 'LPS 0.1 ug/ml', + 'LPS 1.0 ug/ml', + 'LPS 10.0 ug/ml', + 'LPS 100.0 ug/ml', + + 'LPS 1.0 ug/ml + Nigericin 1.0 uM', + 'LPS 1.0 ug/ml + Nigericin 3.0 uM', + 'LPS 1.0 ug/ml + Nigericin 10.0 uM', + + 'LPS 100.0 ug/ml + Nigericin 1.0 uM', + 'LPS 100.0 ug/ml + Nigericin 3.0 uM', + 'LPS 100.0 ug/ml + Nigericin 10.0 uM', + + 'H2O2 100.0 nM', + 'H2O2 100.0 uM', + + 'Disulfiram 0.1 uM', + 'Disulfiram 1.0 uM', + 'Disulfiram 2.5 uM', + + 'Thapsigargin 1.0 uM', + 'Thapsigargin 10.0 uM', + + 'Topotecan 5.0 nM', + 'Topotecan 10.0 nM', + 'Topotecan 20.0 nM' + ), + values = colors) + + scale_shape_manual( + name = "Inhibitor", + labels = c( + 'Media', + 'DMSO 0.025%', + 'DMSO 1.0%', + + 'Disulfiram 0.1 uM', + 'Disulfiram 1.0 uM', + 'Disulfiram 2.5 uM', + + 'Z-VAD-FMK 30.0 uM', + 'Z-VAD-FMK 100.0 uM' + + ), + values = shapes + ) + # make the legend 1 column + + guides(color = guide_legend(ncol = 1), shape = guide_legend(ncol = 1)) + + ggplot2::coord_fixed() + + facet_grid(shuffled~.) + # add y = x line + + geom_abline(intercept = 0, slope = 1, linetype = "dashed", color = "black") +) +scatter_by_treatment diff --git a/9.mAP/scripts/3.aggregate_map_scores_secretome.py b/9.mAP/scripts/3.aggregate_map_scores_secretome.py deleted file mode 100644 index ee13b5ab3..000000000 --- a/9.mAP/scripts/3.aggregate_map_scores_secretome.py +++ /dev/null @@ -1,93 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -import pathlib -import warnings - -import numpy as np -import pandas as pd -import plotly.express as px -from copairs.map import aggregate - -warnings.filterwarnings("ignore") - - -# In[2]: - - -# Directories -processed_data_dir = pathlib.Path("../data/processed/") -sc_ap_scores_dir = (processed_data_dir / "mAP_scores/secretome").resolve() -agg_sc_ap_scores_dir = (processed_data_dir / "aggregate_mAPs/secretome").resolve() -agg_sc_ap_scores_dir.mkdir(parents=True, exist_ok=True) - - -# ## Preparing the dataset -# - -# In[3]: - - -all_files = list(sc_ap_scores_dir.glob("*.csv")) -# get the files that contain the string class -class_files = [file for file in all_files if "class" in file.stem] -mAPs = [] -for file in class_files: - df = pd.read_csv(file) - df["file"] = file.stem - mAPs.append(df) -# single-cell mAP scores -mAPs = pd.concat(mAPs) -mAPs.head() - - -# In[4]: - - -# grabbing all cp features (regular, feature shuffled and labeled shuffled) -reg_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "non-shuffled"] -shuffled_feat_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "features_shuffled"] -shuffled_pheno_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "phenotype_shuffled"] - - -# In[5]: - - -# calculating sampling error -# grouping dataframe based on phenotype levels, feature and feature types -df_group = mAPs.groupby(by=["Metadata_labels", "shuffled"]) - - -sampling_error_df = [] -for name, df in df_group: - pheno, shuffled_type = name - - # caclulating sampling error - avg_percision = df["average_precision"].values - sampling_error = np.std(avg_percision) / np.sqrt(len(avg_percision)) - - sampling_error_df.append([pheno, shuffled_type, sampling_error]) -cols = ["Metadata_labels", "shuffled", "sampling_error"] -sampling_error_df = pd.DataFrame(sampling_error_df, columns=cols) - - -sampling_error_df.head() - - -# In[6]: - - -# Generating aggregate scores with a threshold p-value of 0.05 -mAP_dfs = [] -for name, df in tuple(mAPs.groupby(by=["Metadata_labels", "shuffled"])): - agg_df = aggregate(df, sameby=["Metadata_labels"], threshold=0.05) - agg_df["Metadata_labels"] = name[0] - agg_df["shuffled"] = name[1] - mAP_dfs.append(agg_df) - -mAP_dfs = pd.concat(mAP_dfs) -mAP_dfs.to_csv(agg_sc_ap_scores_dir / "mAP_scores_class.csv", index=False) -mAP_dfs.head() diff --git a/9.mAP/scripts/4.generate_map_scores_morphology_treatment.py b/9.mAP/scripts/4.generate_map_scores_morphology_treatment.py deleted file mode 100644 index 7a7f8ab76..000000000 --- a/9.mAP/scripts/4.generate_map_scores_morphology_treatment.py +++ /dev/null @@ -1,474 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -import itertools -import logging -import pathlib -import sys -from typing import Optional - -import numpy as np -import pandas as pd -import toml -from copairs.map import run_pipeline -from pycytominer import feature_select - -# imports src -sys.path.append("../") -from src import utils - -# setting up logger -logging.basicConfig( - filename="map_analysis_testing.log", - level=logging.DEBUG, - format="%(levelname)s:%(asctime)s:%(name)s:%(message)s", -) - - -# ## Helper functions -# Set of helper functions to help out throughout the notebook - -# In[2]: - - -## Helper function - - -def shuffle_meta_labels( - dataset: pd.DataFrame, target_col: str, seed: Optional[int] = 0 -) -> pd.DataFrame: - """shuffles labels or values within a single selected column - - Parameters - ---------- - dataset : pd.DataFrame - dataframe containing the dataset - - target_col : str - Column to select in order to conduct the shuffling - - seed : int - setting random seed - - Returns - ------- - pd.DataFrame - shuffled dataset - - Raises - ------ - TypeError - raised if incorrect types are provided - """ - # setting seed - np.random.seed(seed) - - # type checking - if not isinstance(target_col, str): - raise TypeError("'target_col' must be a string type") - if not isinstance(dataset, pd.DataFrame): - raise TypeError("'dataset' must be a pandas dataframe") - - # selecting column, shuffle values within column, add to dataframe - # dataset[target_col] = np.random.permutation(dataset[target_col].values) - for column in dataset.columns: - if column == target_col: - np.random.shuffle(dataset[column].values) - return dataset - - -def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.array: - """suffles all values within feature space - - Parameters - ---------- - feature_vals : np.array - shuffled - - seed : Optional[int] - setting random seed - - Returns - ------- - np.array - Returns shuffled values within the feature space - - Raises - ------ - TypeError - Raised if a numpy array is not provided - """ - # setting seed - np.random.seed(seed) - - # shuffle given array - if not isinstance(feature_vals, np.ndarray): - raise TypeError("'feature_vals' must be a numpy array") - if feature_vals.ndim != 2: - raise TypeError("'feature_vals' must be a 2x2 matrix") - - # creating a copy for feature vales to prevent overwriting of global variables - feature_vals = np.copy(feature_vals) - - # shuffling feature space - n_cols = feature_vals.shape[1] - for col_idx in range(0, n_cols): - # selecting column, shuffle, and update: - feature_vals[:, col_idx] = np.random.permutation(feature_vals[:, col_idx]) - - return feature_vals - - -# ## Setting up Paths and loading data - -# In[3]: - - -# load in the treatment groups -ground_truth = pathlib.Path( - "../../4.sc_Morphology_Neural_Network_MLP_Model/MLP_utils/ground_truth.toml" -).resolve(strict=True) -# load in the ground truth -ground_truth = toml.load(ground_truth) -apoptosis_ground_truth = ground_truth["Apoptosis"]["apoptosis_groups_list"] -pyroptosis_ground_truth = ground_truth["Pyroptosis"]["pyroptosis_groups_list"] -control_ground_truth = ground_truth["Healthy"]["healthy_groups_list"] - - -# In[4]: - - -single_cell_data = pathlib.Path( - f"../../data/PBMC_preprocessed_sc_norm_aggregated.parquet" -).resolve(strict=True) -df = pd.read_parquet(single_cell_data) - - -# In[5]: - - -# out paths -map_out_dir = pathlib.Path("../data/processed/mAP_scores/morphology/") -map_out_dir.mkdir(exist_ok=True, parents=True) - -# regular data output -# saving to csv -regular_feat_map_path = pathlib.Path(map_out_dir / "mAP_scores_regular_treatment.csv") - -# shuffled data output -shuffled_feat_map_path = pathlib.Path( - map_out_dir / "mAP_scores_shuffled_class_treatment.csv" -) - -# shuffled feature space output -shuffled_feat_space_map_path = pathlib.Path( - map_out_dir / "mAP_scores_shuffled_feature_space_treatment.csv" -) - - -# ### Clean up data - -# In[6]: - - -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique() -# replace values in the oneb_Metadata_Treatment_Dose_Inhibitor_Dose column -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace( - "Flagellin_0.100_ug_per_ml_DMSO_0.000_%", "Flagellin_0.100_ug_per_ml_DMSO_0.025_%" -) -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace("Flagellin_1.000_0_DMSO_0.025_%", "Flagellin_1.000_ug_per_ml_DMSO_0.025_%") -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace( - "Flagellin_1.000_ug_per_ml_DMSO_0.000_%", "Flagellin_1.000_ug_per_ml_DMSO_0.025_%" -) -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace("media_ctr_0.0_0_Media_0_0", "Media") -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace("media_ctr_0.0_0_Media_ctr_0.0_0", "Media") -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace( - "Flagellin_1.000_0_Disulfiram_1.000_uM", - "Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM", -) -len(df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique()) -# add apoptosis, pyroptosis and healthy columns to dataframe -df["Apoptosis"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in apoptosis_ground_truth, - axis=1, -) -df["Pyroptosis"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in pyroptosis_ground_truth, - axis=1, -) -df["Control"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in control_ground_truth, - axis=1, -) - -# merge apoptosis, pyroptosis, and healthy columns into one column -df["Metadata_labels"] = df.apply( - lambda row: "Apoptosis" - if row["Apoptosis"] - else "Pyroptosis" - if row["Pyroptosis"] - else "Control", - axis=1, -) - -# # drop apoptosis, pyroptosis, and healthy columns -df.drop(columns=["Apoptosis", "Pyroptosis", "Control"], inplace=True) - - -# In[7]: - - -# output directories -map_out_dir = pathlib.Path("../data/processed/mAP_scores/") -map_out_dir.mkdir(parents=True, exist_ok=True) - - -# ## Define the control df - -# In[8]: - - -control_df = df[ - df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] == "DMSO_0.100_%_DMSO_0.025_%" -] -control_df - - -# ### mAP Pipeline Parameters - -# The null size needs to be determined for the mAP pipeline. This is the size of the null class that is used to determine the mAP score. - -# In[9]: - - -tmp = ( - df.groupby(["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"]) - .count() - .reset_index()[["Metadata_Well", "oneb_Metadata_Treatment_Dose_Inhibitor_Dose"]] -) -# get the counts of each oneb_Metadata_Treatment_Dose_Inhibitor_Dose -min_count = tmp["Metadata_Well"].min() -print(min_count) - - -# Positive pairs: profiles in the same group -# Negative pairs: profiles in different groups -# -# -# pos_sameby = Treatment group: All profiles that have the same treatment group -# pos_diffby = Treatment replicates: In this case - wells -# -# - -# In[10]: - - -pos_sameby = ["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] -pos_diffby = ["Metadata_Well"] - -neg_sameby = [] -neg_diffby = ["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - -# null_size = min_count -null_size = 100000 -batch_size = 1 - - -# ### mAP analysis for non-shuffled data - -# Loop through the data and determine the mAP score for each treatment in a class compared to a whole other class -# Ex. Pyroptosis treatment 1 (LPS 1.0 ug/mL) vs. All Apoptosis treatments -# Ex. Pyroptosis treatment 1 (LPS 1.0 ug/mL) vs. All Control treatments - -# In[11]: - - -results_df = pd.DataFrame( - columns=[ - "Metadata_Well", - "Metadata_labels", - "average_precision", - "p_value", - "n_pos_pairs", - "n_total_pairs", - "shuffled", - "comparison", - ] -) - - -# In[12]: - - -# remove the control group from the dataframe -df = df[ - df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] != "DMSO_0.100_%_DMSO_0.025_%" -] - - -# In[13]: - - -for i in df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique(): - # manually get treatment - tmp = df[df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].str.contains(i)] - - # concat tmp and concrol_df - tmp1 = pd.concat([tmp, control_df]) - print(tmp1["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique()) - # order the oneb_Metadata_Treatment_Dose_Inhibitor_Dose column so that the control group is at the beginning - tmp1["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = pd.Categorical( - tmp1["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"], - categories=["DMSO_0.100_%_DMSO_0.025_%", i], - ordered=True, - ) - - # spliting metadata and raw feature values - logging.info("splitting data set into metadata and raw feature values") - df_meta, df_feats = utils.split_data(tmp1) - df_feats = np.array(df_feats) - try: - # execute pipeline on negative control with trianing dataset with cp features - - logging.info(f"Running pipeline on CP features using phenotype") - result = run_pipeline( - meta=df_meta, - feats=df_feats, - pos_sameby=pos_sameby, - pos_diffby=pos_diffby, - neg_sameby=neg_sameby, - neg_diffby=neg_diffby, - batch_size=batch_size, - null_size=null_size, - ) - - result["shuffled"] = "non-shuffled" - result["comparison"] = i - - except ZeroDivisionError as e: - logging.warning(f"{e} captured on phenotye:. Skipping") - - # concatenating all datasets - results_df = pd.concat([results_df, result], axis=0) -results_df.to_csv(regular_feat_map_path, index=False) - - -# In[14]: - - -result - - -# In[ ]: - - -# In[15]: - - -import matplotlib.pyplot as plt - -# plot the average precision scores on a number line -import seaborn as sns - -# plot the average precision scores -sns.set(style="whitegrid") -plt.figure(figsize=(10, 5)) -ax = sns.barplot( - x="comparison", y="average_precision", hue="Metadata_Well", data=result -) -plt.title("Average Precision Scores") -# legend on the right -plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0) -plt.show() - - -# In[16]: - - -results_df.head(15) - - -# ### mAP analysis for shuffled data (Feature space) - -# In[17]: - - -results_df = pd.DataFrame( - columns=[ - "Metadata_Well", - "Metadata_labels", - "average_precision", - "p_value", - "n_pos_pairs", - "n_total_pairs", - "shuffled", - "comparison", - ] -) - - -# In[18]: - - -for i in df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique(): - # manually get treatment - tmp = df[ - df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].str.contains(i) - ].reset_index(drop=True) - - # concat tmp and concrol_df - tmp1 = pd.concat([tmp, control_df]).reset_index(drop=True) - - # spliting metadata and raw feature values - logging.info("splitting data set into metadata and raw feature values") - df_meta, df_feats = utils.split_data(tmp1) - df_feats = np.array(df_feats) - seed = np.random.randint(0, 100) - - # shuffling the features, this will overwrite the generated feature space from above with the shuffled one - df_feats = shuffle_features(feature_vals=df_feats, seed=seed) - - try: - # execute pipeline on negative control with trianing dataset with cp features - - logging.info(f"Running pipeline on CP features using phenotype") - result = run_pipeline( - meta=df_meta, - feats=df_feats, - pos_sameby=pos_sameby, - pos_diffby=pos_diffby, - neg_sameby=neg_sameby, - neg_diffby=neg_diffby, - batch_size=batch_size, - null_size=null_size, - ) - - result["shuffled"] = "shuffled" - result["comparison"] = i - - except ZeroDivisionError as e: - logging.warning(f"{e} captured on phenotye:. Skipping") - - # concatenating all datasets - results_df = pd.concat([results_df, result], ignore_index=True) -# saving to csv -results_df.to_csv(shuffled_feat_space_map_path, index=False) -results_df.head(10) diff --git a/9.mAP/scripts/5.aggregate_map_scores_morphology_treatment.py b/9.mAP/scripts/5.aggregate_map_scores_morphology_treatment.py deleted file mode 100644 index 982943978..000000000 --- a/9.mAP/scripts/5.aggregate_map_scores_morphology_treatment.py +++ /dev/null @@ -1,94 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -import pathlib -import warnings - -import numpy as np -import pandas as pd -import plotly.express as px -from copairs.map import aggregate - -warnings.filterwarnings("ignore") - - -# In[2]: - - -# Directories -processed_data_dir = pathlib.Path("../data/processed/") -sc_ap_scores_dir = (processed_data_dir / "mAP_scores/morphology").resolve() -agg_sc_ap_scores_dir = (processed_data_dir / "aggregate_mAPs/morphology").resolve() -agg_sc_ap_scores_dir.mkdir(parents=True, exist_ok=True) - - -# ## Preparing the dataset -# - -# In[3]: - - -all_files = list(sc_ap_scores_dir.glob("*.csv")) -# get the files that contain the string class -class_files = [file for file in all_files if "treatment" in file.stem] -mAPs = [] -for file in class_files: - df = pd.read_csv(file) - df["file"] = file.stem - mAPs.append(df) -# single-cell mAP scores -mAPs = pd.concat(mAPs) -mAPs.head() - - -# In[4]: - - -# grabbing all cp features (regular, feature shuffled and labeled shuffled) -reg_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "non-shuffled"] -shuffled_feat_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "features_shuffled"] - - -# In[6]: - - -# grouping dataframe based on phenotype levels, feature and feature types -df_group = mAPs.groupby(by=["oneb_Metadata_Treatment_Dose_Inhibitor_Dose", "shuffled"]) - -# calculating sampling error -sampling_error_df = [] -for name, df in df_group: - pheno, shuffled_type = name - - # caclulating sampling error - avg_percision = df["average_precision"].values - sampling_error = np.std(avg_percision) / np.sqrt(len(avg_percision)) - - sampling_error_df.append([pheno, shuffled_type, sampling_error]) -cols = ["oneb_Metadata_Treatment_Dose_Inhibitor_Dose", "shuffled", "sampling_error"] -sampling_error_df = pd.DataFrame(sampling_error_df, columns=cols) - -sampling_error_df.head() - - -# In[8]: - - -# Generating aggregate scores with a threshold p-value of 0.05 -mAP_dfs = [] -for name, df in tuple( - mAPs.groupby(by=["oneb_Metadata_Treatment_Dose_Inhibitor_Dose", "shuffled"]) -): - agg_df = aggregate( - df, sameby=["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"], threshold=0.05 - ) - agg_df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = name[0] - agg_df["shuffled"] = name[1] - mAP_dfs.append(agg_df) - -mAP_dfs = pd.concat(mAP_dfs) -mAP_dfs.to_csv(agg_sc_ap_scores_dir / "mAP_scores_treatment.csv", index=False) -mAP_dfs.head() diff --git a/9.mAP/scripts/6.generate_map_scores_secretome_treatment.py b/9.mAP/scripts/6.generate_map_scores_secretome_treatment.py deleted file mode 100644 index 0b2a62c34..000000000 --- a/9.mAP/scripts/6.generate_map_scores_secretome_treatment.py +++ /dev/null @@ -1,477 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -import itertools -import logging -import pathlib -import sys -from typing import Optional - -import numpy as np -import pandas as pd -import toml -from copairs.map import run_pipeline -from pycytominer import feature_select - -# imports src -sys.path.append("../") -from src import utils - -# setting up logger -logging.basicConfig( - filename="map_analysis_testing.log", - level=logging.DEBUG, - format="%(levelname)s:%(asctime)s:%(name)s:%(message)s", -) - - -# ## Helper functions -# Set of helper functions to help out throughout the notebook - -# In[2]: - - -## Helper function - - -def shuffle_meta_labels( - dataset: pd.DataFrame, target_col: str, seed: Optional[int] = 0 -) -> pd.DataFrame: - """shuffles labels or values within a single selected column - - Parameters - ---------- - dataset : pd.DataFrame - dataframe containing the dataset - - target_col : str - Column to select in order to conduct the shuffling - - seed : int - setting random seed - - Returns - ------- - pd.DataFrame - shuffled dataset - - Raises - ------ - TypeError - raised if incorrect types are provided - """ - # setting seed - np.random.seed(seed) - - # type checking - if not isinstance(target_col, str): - raise TypeError("'target_col' must be a string type") - if not isinstance(dataset, pd.DataFrame): - raise TypeError("'dataset' must be a pandas dataframe") - - # selecting column, shuffle values within column, add to dataframe - dataset[target_col] = np.random.permutation(dataset[target_col].values) - return dataset - - -def shuffle_features(feature_vals: np.array, seed: Optional[int] = 0) -> np.array: - """suffles all values within feature space - - Parameters - ---------- - feature_vals : np.array - shuffled - - seed : Optional[int] - setting random seed - - Returns - ------- - np.array - Returns shuffled values within the feature space - - Raises - ------ - TypeError - Raised if a numpy array is not provided - """ - # setting seed - np.random.seed(seed) - - # shuffle given array - if not isinstance(feature_vals, np.ndarray): - raise TypeError("'feature_vals' must be a numpy array") - if feature_vals.ndim != 2: - raise TypeError("'feature_vals' must be a 2x2 matrix") - - # creating a copy for feature vales to prevent overwriting of global variables - feature_vals = np.copy(feature_vals) - - # shuffling feature space - n_cols = feature_vals.shape[1] - for col_idx in range(0, n_cols): - # selecting column, shuffle, and update: - feature_vals[:, col_idx] = np.random.permutation(feature_vals[:, col_idx]) - - return feature_vals - - -# ## Setting up Paths and loading data - -# In[3]: - - -# load in the treatment groups -ground_truth = pathlib.Path( - "../../4.sc_Morphology_Neural_Network_MLP_Model/MLP_utils/ground_truth.toml" -).resolve(strict=True) -# load in the ground truth -ground_truth = toml.load(ground_truth) -apoptosis_ground_truth = ground_truth["Apoptosis"]["apoptosis_groups_list"] -pyroptosis_ground_truth = ground_truth["Pyroptosis"]["pyroptosis_groups_list"] -control_ground_truth = ground_truth["Healthy"]["healthy_groups_list"] - - -# In[4]: - - -single_cell_data = pathlib.Path( - f"../../2.Nomic_nELISA_Analysis/Data/clean/Plate2/nELISA_plate_430420_PBMC_clean.parquet" -).resolve(strict=True) -df = pd.read_parquet(single_cell_data) - - -# In[5]: - - -df - - -# In[6]: - - -# rename columns -df = df.rename( - columns={ - "position_x": "Metadata_Well", - "oneb_Treatment_Dose_Inhibitor_Dose": "oneb_Metadata_Treatment_Dose_Inhibitor_Dose", - } -) - - -# In[7]: - - -# out paths -map_out_dir = pathlib.Path("../data/processed/mAP_scores/secretome/") -map_out_dir.mkdir(exist_ok=True, parents=True) - -# regular data output -# saving to csv -regular_feat_map_path = pathlib.Path(map_out_dir / "mAP_scores_regular_treatment.csv") - -# shuffled data output -shuffled_feat_map_path = pathlib.Path(map_out_dir / "mAP_scores_shuffled_treatment.csv") - -# shuffled feature space output -shuffled_feat_space_map_path = pathlib.Path( - map_out_dir / "mAP_scores_shuffled_feature_space_treatment.csv" -) - - -# ### Clean up data - -# In[8]: - - -# keep columns that contain Metdata and ['NSU'] -df = df.filter(regex="Metadata|NSU") -df.head() - -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique() -# replace values in the oneb_Metadata_Treatment_Dose_Inhibitor_Dose column -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace( - "Flagellin_0.100_ug_per_ml_DMSO_0.000_%", "Flagellin_0.100_ug_per_ml_DMSO_0.025_%" -) -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace( - "Flagellin_0.100_ug_per_ml_DMSO_0.0_%", "Flagellin_0.100_ug_per_ml_DMSO_0.025_%" -) -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace( - "Flagellin_1.000_ug_per_ml_DMSO_0.0_%", "Flagellin_1.000_ug_per_ml_DMSO_0.025_%" -) -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace("Flagellin_1.000_0_DMSO_0.025_%", "Flagellin_1.000_ug_per_ml_DMSO_0.025_%") -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace( - "Flagellin_1.000_ug_per_ml_DMSO_0.000_%", "Flagellin_1.000_ug_per_ml_DMSO_0.025_%" -) -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace("media_ctr_0.0_0_Media_0_0", "Media") -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace("media_ctr_0.0_0_Media_ctr_0.0_0", "Media") -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace( - "Flagellin_1.000_0_Disulfiram_1.000_uM", - "Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM", -) -df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = df[ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose" -].replace("media_ctr_0.0_0_Media_0.0_0", "Media") -print(len(df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique())) - - -# In[9]: - - -# add apoptosis, pyroptosis and healthy columns to dataframe -df["Apoptosis"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in apoptosis_ground_truth, - axis=1, -) -df["Pyroptosis"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in pyroptosis_ground_truth, - axis=1, -) -df["Control"] = df.apply( - lambda row: row["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] - in control_ground_truth, - axis=1, -) - -# merge apoptosis, pyroptosis, and healthy columns into one column -df["Metadata_labels"] = df.apply( - lambda row: "Apoptosis" - if row["Apoptosis"] - else "Pyroptosis" - if row["Pyroptosis"] - else "Control", - axis=1, -) -# # drop apoptosis, pyroptosis, and healthy columns -df.drop(columns=["Apoptosis", "Pyroptosis", "Control"], inplace=True) - - -# In[10]: - - -# output directories -map_out_dir = pathlib.Path("../data/processed/mAP_scores/") -map_out_dir.mkdir(parents=True, exist_ok=True) - - -# ### mAP Pipeline Parameters - -# The null size needs to be determined for the mAP pipeline. This is the size of the null class that is used to determine the mAP score. - -# In[11]: - - -tmp = ( - df.groupby(["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"]) - .count() - .reset_index()[["Metadata_Well", "oneb_Metadata_Treatment_Dose_Inhibitor_Dose"]] -) -# get the Pyroptosis number of Metadata_Well -# get the counts of each oneb_Metadata_Treatment_Dose_Inhibitor_Dose -min_count = tmp["Metadata_Well"].min() -print(min_count) -tmp - - -# In[12]: - - -# generate the permutations of cell death labels via itertools -pos_samby_permutations = list(itertools.combinations(df["Metadata_labels"].unique(), 2)) -pos_samby_permutations - - -# In[13]: - - -pos_sameby = ["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] -pos_diffby = ["Metadata_Well"] - -neg_sameby = ["Metadata_labels"] -neg_diffby = [ - "oneb_Metadata_Treatment_Dose_Inhibitor_Dose", -] - -null_size = min_count -batch_size = 1 - -# number of resampling -n_resamples = 10 - - -# ### mAP analysis for non-shuffled data - -# In[14]: - - -results_df = pd.DataFrame( - columns=[ - "Metadata_Well", - "Metadata_labels", - "average_precision", - "p_value", - "n_pos_pairs", - "n_total_pairs", - "shuffled", - "comparison", - ] -) - - -# In[15]: - - -for i in df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique(): - - # manually get treatment - tmp = df[ - df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].str.contains(i) - ].reset_index(drop=True) - # get the label - label = tmp["Metadata_labels"].unique().tolist()[0] - # add all labels to the df except for the LPS treatment label - tmp1 = df[~df["Metadata_labels"].str.contains(label)].reset_index(drop=True) - # concat tmp and tmp1 - tmp1 = pd.concat([tmp, tmp1]).reset_index(drop=True) - - # drop rows that contain the label - _pos_samby_permutations = [x for x in pos_samby_permutations if label in x] - - for j in _pos_samby_permutations: - tmp1 = tmp1[tmp1["Metadata_labels"].isin(j)].reset_index(drop=True) - - # spliting metadata and raw feature values - logging.info("splitting data set into metadata and raw feature values") - df_meta, df_feats = utils.split_data(tmp1) - df_feats = np.array(df_feats) - try: - # execute pipeline on negative control with trianing dataset with cp features - - logging.info(f"Running pipeline on CP features using phenotype") - result = run_pipeline( - meta=df_meta, - feats=df_feats, - pos_sameby=pos_sameby, - pos_diffby=pos_diffby, - neg_sameby=neg_sameby, - neg_diffby=neg_diffby, - batch_size=batch_size, - null_size=null_size, - ) - - result["shuffled"] = "non-shuffled" - comparison = i - comparison = comparison + "_" + "_vs_".join(j) - - result["comparison"] = comparison - - except ZeroDivisionError as e: - logging.warning(f"{e} captured on phenotye:. Skipping") - - # concatenating all datasets - results_df = pd.concat([results_df, result], ignore_index=True) -results_df.to_csv(regular_feat_map_path, index=False) -results_df.head() - - -# ### mAP analysis for shuffled data (Phenotype) - -# In[16]: - - -results_df = pd.DataFrame( - columns=[ - "Metadata_Well", - "Metadata_labels", - "average_precision", - "p_value", - "n_pos_pairs", - "n_total_pairs", - "shuffled", - "comparison", - ] -) - - -# In[17]: - - -for i in df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].unique(): - - # manually get treatment - tmp = df[ - df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"].str.contains(i) - ].reset_index(drop=True) - # get the label - label = tmp["Metadata_labels"].unique().tolist()[0] - # add all labels to the df except for the LPS treatment label - tmp1 = df[~df["Metadata_labels"].str.contains(label)].reset_index(drop=True) - # concat tmp and tmp1 - tmp1 = pd.concat([tmp, tmp1]).reset_index(drop=True) - - # drop rows that contain the label - _pos_samby_permutations = [x for x in pos_samby_permutations if label in x] - - for j in _pos_samby_permutations: - tmp1 = tmp1[tmp1["Metadata_labels"].isin(j)].reset_index(drop=True) - - # spliting metadata and raw feature values - logging.info("splitting data set into metadata and raw feature values") - df_meta, df_feats = utils.split_data(tmp1) - df_feats = np.array(df_feats) - seed = np.random.randint(0, 100) - - # shuffling the features, this will overwrite the generated feature space from above with the shuffled one - df_feats = shuffle_features(feature_vals=df_feats, seed=seed) - - try: - # execute pipeline on negative control with trianing dataset with cp features - - logging.info(f"Running pipeline on CP features using phenotype") - result = run_pipeline( - meta=df_meta, - feats=df_feats, - pos_sameby=pos_sameby, - pos_diffby=pos_diffby, - neg_sameby=neg_sameby, - neg_diffby=neg_diffby, - batch_size=batch_size, - null_size=null_size, - ) - - result["shuffled"] = "shuffled" - comparison = i - comparison = comparison + "_" + "_vs_".join(j) - - result["comparison"] = comparison - - except ZeroDivisionError as e: - logging.warning(f"{e} captured on phenotye:. Skipping") - - # concatenating all datasets - results_df = pd.concat([results_df, result], ignore_index=True) - -# saving to csv -results_df.to_csv(shuffled_feat_space_map_path, index=False) -results_df diff --git a/9.mAP/scripts/7.aggregate_map_scores_secretome_treatment.py b/9.mAP/scripts/7.aggregate_map_scores_secretome_treatment.py deleted file mode 100644 index a2d21d819..000000000 --- a/9.mAP/scripts/7.aggregate_map_scores_secretome_treatment.py +++ /dev/null @@ -1,94 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -import pathlib -import warnings - -import numpy as np -import pandas as pd -import plotly.express as px -from copairs.map import aggregate - -warnings.filterwarnings("ignore") - - -# In[2]: - - -# Directories -processed_data_dir = pathlib.Path("../data/processed/") -sc_ap_scores_dir = (processed_data_dir / "mAP_scores/secretome").resolve() -agg_sc_ap_scores_dir = (processed_data_dir / "aggregate_mAPs/secretome").resolve() -agg_sc_ap_scores_dir.mkdir(parents=True, exist_ok=True) - - -# ## Preparing the dataset -# - -# In[3]: - - -all_files = list(sc_ap_scores_dir.glob("*.csv")) -# get the files that contain the string class -class_files = [file for file in all_files if "treatment" in file.stem] -mAPs = [] -for file in class_files: - df = pd.read_csv(file) - df["file"] = file.stem - mAPs.append(df) -# single-cell mAP scores -mAPs = pd.concat(mAPs) -mAPs.head() - - -# In[4]: - - -# grabbing all cp features (regular, feature shuffled and labeled shuffled) -reg_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "non-shuffled"] -shuffled_feat_sc_mAPs = mAPs.loc[mAPs["shuffled"] == "features_shuffled"] - - -# In[5]: - - -# grouping dataframe based on phenotype levels, feature and feature types -df_group = mAPs.groupby(by=["oneb_Metadata_Treatment_Dose_Inhibitor_Dose", "shuffled"]) - -# calculating sampling error -sampling_error_df = [] -for name, df in df_group: - pheno, shuffled_type = name - - # caclulating sampling error - avg_percision = df["average_precision"].values - sampling_error = np.std(avg_percision) / np.sqrt(len(avg_percision)) - - sampling_error_df.append([pheno, shuffled_type, sampling_error]) -cols = ["oneb_Metadata_Treatment_Dose_Inhibitor_Dose", "shuffled", "sampling_error"] -sampling_error_df = pd.DataFrame(sampling_error_df, columns=cols) - -sampling_error_df.head() - - -# In[7]: - - -# Generating aggregate scores with a threshold p-value of 0.05 -mAP_dfs = [] -for name, df in tuple( - mAPs.groupby(by=["oneb_Metadata_Treatment_Dose_Inhibitor_Dose", "shuffled"]) -): - agg_df = aggregate( - df, sameby=["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"], threshold=0.05 - ) - agg_df["oneb_Metadata_Treatment_Dose_Inhibitor_Dose"] = name[0] - agg_df["shuffled"] = name[1] - mAP_dfs.append(agg_df) - -mAP_dfs = pd.concat(mAP_dfs) -mAP_dfs.to_csv(agg_sc_ap_scores_dir / "mAP_scores_treatment.csv", index=False) -mAP_dfs.head() diff --git a/9.mAP/scripts/8.visualize_map_scores.r b/9.mAP/scripts/8.visualize_map_scores.r deleted file mode 100644 index 0f7882859..000000000 --- a/9.mAP/scripts/8.visualize_map_scores.r +++ /dev/null @@ -1,537 +0,0 @@ -suppressPackageStartupMessages(suppressWarnings(library(ggplot2))) -suppressPackageStartupMessages(suppressWarnings(library(RColorBrewer))) -suppressPackageStartupMessages(suppressWarnings(library(dplyr))) -suppressPackageStartupMessages(suppressWarnings(library(tidyr))) -source("../../figures/utils/figure_themes.r") - -width <- 8 -height <- 6 -options(repr.plot.width=width, repr.plot.height=height) - -# set path to the data morphology -# class -df_morphology_class_path <- file.path("..","data","processed","aggregate_mAPs","morphology","mAP_scores_class.csv") -reg_df_morphology_class_path <- file.path("..","data","processed","mAP_scores","morphology","mAP_scores_regular_class.csv") -shuffled_morphology_class_path <- file.path("..","data","processed","mAP_scores","morphology","mAP_scores_shuffled_feature_space_class.csv") -# treatment -treatment_df_morphology_treatment_path <- file.path("..","data","processed","aggregate_mAPs","morphology","mAP_scores_treatment.csv") -reg_df_morphology_treatment_path <- file.path("..","data","processed","mAP_scores","morphology","mAP_scores_regular_treatment.csv") -shuffled_morphology_treatment_path <- file.path("..","data","processed","mAP_scores","morphology","mAP_scores_shuffled_feature_space_treatment.csv") - -# set path to the secretome data -# class -df_secretome_class_path <- file.path("..","data","processed","aggregate_mAPs","secretome","mAP_scores_class.csv") -reg_df_secretome_class_path <- file.path("..","data","processed","mAP_scores","secretome","mAP_scores_regular_class.csv") -shuffled_secretome_class_path <- file.path("..","data","processed","mAP_scores","secretome","mAP_scores_shuffled_feature_space_class.csv") -# treatment -treatment_df_secretome_treatment_path <- file.path("..","data","processed","aggregate_mAPs","secretome","mAP_scores_treatment.csv") -reg_df_secretome_treatment_path <- file.path("..","data","processed","mAP_scores","secretome","mAP_scores_regular_treatment.csv") -shuffled_secretome_treatment_path <- file.path("..","data","processed","mAP_scores","secretome","mAP_scores_shuffled_feature_space_treatment.csv") - -# read in the data -df_morphology_class <- read.csv(df_morphology_class_path) -reg_df_morphology_class <- read.csv(reg_df_morphology_class_path) -shuffled_morphology_class <- read.csv(shuffled_morphology_class_path) - -df_morphology_treatment <- read.csv(treatment_df_morphology_treatment_path) -reg_df_morphology_treatment <- read.csv(reg_df_morphology_treatment_path) -shuffled_morphology_treatment <- read.csv(shuffled_morphology_treatment_path) - -df_secretome_class <- read.csv(df_secretome_class_path) -reg_df_secretome_class <- read.csv(reg_df_secretome_class_path) -shuffled_secretome_class <- read.csv(shuffled_secretome_class_path) - -df_secretome_treatment <- read.csv(treatment_df_secretome_treatment_path) -reg_df_secretome_treatment <- read.csv(reg_df_secretome_treatment_path) -shuffled_secretome_treatment <- read.csv(shuffled_secretome_treatment_path) - -unique(df_morphology_class$shuffled) -unique(df_morphology_treatment$shuffled) -unique(df_secretome_class$shuffled) -unique(df_secretome_treatment$shuffled) - -levels_list <- c( - 'Media', - 'DMSO_0.100_%_DMSO_0.025_%', - 'DMSO_0.100_%_DMSO_1.000_%', - 'DMSO_0.100_%_Z-VAD-FMK_30.000_uM', - 'DMSO_0.100_%_Z-VAD-FMK_100.000_uM', - - 'Disulfiram_0.100_uM_DMSO_0.025_%', - 'Disulfiram_1.000_uM_DMSO_0.025_%', - 'Disulfiram_2.500_uM_DMSO_0.025_%', - - 'Flagellin_0.100_ug_per_ml_DMSO_0.025_%', - 'Flagellin_1.000_ug_per_ml_DMSO_0.025_%', - 'Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM', - - 'LPS_0.010_ug_per_ml_DMSO_0.025_%', - 'LPS_0.100_ug_per_ml_DMSO_0.025_%', - 'LPS_1.000_ug_per_ml_DMSO_0.025_%', - - 'LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM', - 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM', - - 'LPS_10.000_ug_per_ml_DMSO_0.025_%', - 'LPS_10.000_ug_per_ml_Disulfiram_0.100_uM', - 'LPS_10.000_ug_per_ml_Disulfiram_1.000_uM', - 'LPS_10.000_ug_per_ml_Disulfiram_2.500_uM', - 'LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM', - - 'LPS_100.000_ug_per_ml_DMSO_0.025_%', - 'LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%', - - 'H2O2_100.000_nM_DMSO_0.025_%', - 'H2O2_100.000_uM_DMSO_0.025_%', - 'H2O2_100.000_uM_Disulfiram_1.000_uM', - 'H2O2_100.000_uM_Z-VAD-FMK_100.000_uM', - 'Thapsigargin_1.000_uM_DMSO_0.025_%', - 'Thapsigargin_10.000_uM_DMSO_0.025_%', - - 'Topotecan_5.000_nM_DMSO_0.025_%', - 'Topotecan_10.000_nM_DMSO_0.025_%', - 'Topotecan_20.000_nM_DMSO_0.025_%' -) - -# declare the shuffled column as a factor -# replace the values in the shuffled column -# declare the shuffled column as a factor -# replace the values in the shuffled column -df_morphology_class$shuffled <- gsub("shuffled", "Shuffled", df_morphology_class$shuffled) -df_morphology_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", df_morphology_class$shuffled) -df_morphology_class$shuffled <- factor(df_morphology_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) -df_morphology_class$Metadata_labels <- factor(df_morphology_class$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) - -df_secretome_class$shuffled <- gsub("shuffled", "Shuffled", df_secretome_class$shuffled) -df_secretome_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", df_secretome_class$shuffled) -df_secretome_class$shuffled <- factor(df_secretome_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) -df_secretome_class$Metadata_labels <- factor(df_secretome_class$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) - -df_morphology_treatment$shuffled <- gsub("shuffled", "Shuffled", df_morphology_treatment$shuffled) -df_morphology_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", df_morphology_treatment$shuffled) -df_morphology_treatment$shuffled <- factor(df_morphology_treatment$shuffled, levels = c( "Non-shuffled", "Shuffled")) -df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - -df_secretome_treatment$shuffled <- gsub("shuffled", "Shuffled", df_secretome_treatment$shuffled) -df_secretome_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", df_secretome_treatment$shuffled) -df_secretome_treatment$shuffled <- factor(df_secretome_treatment$shuffled, levels = c("Non-shuffled", "Shuffled")) -df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - - -unique(df_morphology_class$shuffled) -unique(df_morphology_treatment$shuffled) -unique(df_secretome_class$shuffled) -unique(df_secretome_treatment$shuffled) - -width <- 10 -height <- 5 -options(repr.plot.width=width, repr.plot.height=height) -# define the barplot function -barplot_function <- function(df, x,title, y_label, x_label, legend_title){ - x <- sym(x) - barplot <- ( - ggplot(df, aes(x=!!x, y=mean_average_precision, fill=shuffled)) - + geom_bar(stat="identity", position="dodge") - + labs(x=x_label, y=y_label) - # legend title - + scale_fill_discrete(name=legend_title) - + theme_bw() - + ylim(0,1) - + ggtitle(title) - + figure_theme - ) - return(barplot) -} - -barplot_morphology_class <- barplot_function(df_morphology_class, "Metadata_labels","Morphology class", "Mean average precision", "Class", "Shuffle type") -barplot_morphology_treatment <- barplot_function(df_morphology_treatment, "oneb_Metadata_Treatment_Dose_Inhibitor_Dose","Morphology treatment", "Mean average precision", "Treatment", "Shuffle type") -barplot_secretome_class <- barplot_function(df_secretome_class, "Metadata_labels","Secretome class", "Mean average precision", "Class", "Shuffle type") -barplot_secretome_treatment <- barplot_function(df_secretome_treatment, "oneb_Metadata_Treatment_Dose_Inhibitor_Dose","Secretome treatment", "Mean average precision", "Treatment", "Shuffle type") - -barplot_morphology_class -barplot_morphology_treatment -barplot_secretome_class -barplot_secretome_treatment - - -# combine the dataframes -all_df_morphology_class <- rbind(reg_df_morphology_class, shuffled_morphology_class) -all_df_morphology_treatment <- rbind(reg_df_morphology_treatment, shuffled_morphology_treatment) -all_df_secretome_class <- rbind(reg_df_secretome_class, shuffled_secretome_class) -all_df_secretome_treatment <- rbind(reg_df_secretome_treatment, shuffled_secretome_treatment) - -all_df_morphology_class$shuffled <- gsub("shuffled", "Shuffled", all_df_morphology_class$shuffled) -all_df_morphology_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_morphology_class$shuffled) -all_df_morphology_class$shuffled <- factor(all_df_morphology_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_morphology_class$Metadata_labels <- factor(all_df_morphology_class$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) - -all_df_secretome_class$shuffled <- gsub("shuffled", "Shuffled", all_df_secretome_class$shuffled) -all_df_secretome_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_secretome_class$shuffled) -all_df_secretome_class$shuffled <- factor(all_df_secretome_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) - -all_df_morphology_treatment$shuffled <- gsub("shuffled", "Shuffled", all_df_morphology_treatment$shuffled) -all_df_morphology_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_morphology_treatment$shuffled) -all_df_morphology_treatment$shuffled <- factor(all_df_morphology_treatment$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - -all_df_secretome_treatment$shuffled <- gsub("shuffled", "Shuffled", all_df_secretome_treatment$shuffled) -all_df_secretome_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_secretome_treatment$shuffled) -all_df_secretome_treatment$shuffled <- factor(all_df_secretome_treatment$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - -unique(all_df_secretome_class$shuffled) - -head(all_df_morphology_class) - -# cobine the dfs -# get the average precision, shuffled, and Metadata_labels columns by name -subset_morphology_class <- all_df_morphology_class[,c("average_precision", "shuffled", "Metadata_labels")] -# rename the average_precision column to moprhology_ap -colnames(subset_morphology_class)[colnames(subset_morphology_class)=="average_precision"] <- "morphology_ap" - -# get the average precision, shuffled, and Metadata_labels columns by name -subset_secretome_class <- all_df_secretome_class[,c("average_precision", "shuffled", "Metadata_labels")] -# rename the average_precision column to secretome_ap -colnames(subset_secretome_class)[colnames(subset_secretome_class)=="average_precision"] <- "secretome_ap" - -# merge the dataframes -merged_df <- merge(subset_morphology_class, subset_secretome_class, by=c("shuffled", "Metadata_labels")) -head(merged_df) - - -# aggregate the data by shuffled and Metadata_labels -merged_agg <- aggregate(. ~ shuffled + Metadata_labels, data=merged_df, FUN=mean) -# combine the shuffled and Metadata_labels columns -merged_agg$group <- paste(merged_agg$shuffled, merged_agg$Metadata_labels, sep="_") -# change the text in the group column -merged_agg$group <- gsub("Non-shuffled Control", "Non-shuffled\nControl", merged_agg$group) -merged_agg$group <- gsub("Shuffled Control", "Shuffled\nControl", merged_agg$group) -merged_agg$group <- gsub("Non-shuffled_Apoptosis", "Non-shuffled\nApoptosis", merged_agg$group) -merged_agg$group <- gsub("Shuffled Apoptosis", "Shuffled\nApoptosis", merged_agg$group) -merged_agg$group <- gsub("Non-shuffled Pyroptosis", "Non-shuffled\nPyroptosis", merged_agg$group) -merged_agg$group <- gsub("Shuffled Pyroptosis", "Shuffled\nPyroptosis", merged_agg$group) -# make the group column a factor -merged_agg$group <- factor( - merged_agg$group, - levels = c( - "Non-shuffled\nControl", - "Shuffled features\nControl", - "Shuffled phenotypes\nControl", - - "Non-shuffled\nApoptosis", - "Shuffled features\nApoptosis", - "Shuffled phenotypes\nApoptosis", - - "Non-shuffled\nPyroptosis", - "Shuffled features\nPyroptosis", - "Shuffled phenotypes\nPyroptosis")) - -merged_agg - -width <- 8 -height <- 6 -options(repr.plot.width=width, repr.plot.height=height) -# plot the data -scatter_compare <- ( - ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled)) - + geom_point(size=3, alpha=1) - + labs(x="Morphology mAP score", y="Secretome mAP score") - + theme_bw() - + ggtitle("Comparison of mAP scores") - + ylim(0,1) - + xlim(0,1) - # Change the legend title - # change the legend shape - + scale_shape_manual( - name="Shuffle type", - labels=c( - "Non-shuffled", - "Shuffled features", - "Shuffled phenotypes" - ), - values=c(19, 17, 15) - ) - + scale_color_manual( - name="Class", - labels=c( - "Control", - "Apoptosis", - "Pyroptosis" - ), - values=c( - brewer.pal(3, "Dark2")[2], - brewer.pal(3, "Dark2")[1], - brewer.pal(3, "Dark2")[3] - ) -) - + figure_theme - # add y = x line - + geom_abline(intercept = 0, slope = 1, linetype="dashed") - -) -scatter_compare - -# cobine the dfs -# get the average precision, shuffled, and Metadata_labels columns by name -subset_morphology_treatment <- all_df_morphology_treatment[,c("average_precision", "shuffled", "Metadata_labels","oneb_Metadata_Treatment_Dose_Inhibitor_Dose")] -# rename the average_precision column to moprhology_ap -colnames(subset_morphology_treatment)[colnames(subset_morphology_treatment)=="average_precision"] <- "morphology_ap" - -# get the average precision, shuffled, and Metadata_labels columns by name -subset_secretome_treatment <- all_df_secretome_treatment[,c("average_precision", "shuffled", "Metadata_labels","oneb_Metadata_Treatment_Dose_Inhibitor_Dose")] -# rename the average_precision column to secretome_ap -colnames(subset_secretome_treatment)[colnames(subset_secretome_treatment)=="average_precision"] <- "secretome_ap" - -# merge the dataframes -merged_df <- merge(subset_morphology_treatment, subset_secretome_treatment, by=c("shuffled", "Metadata_labels", "oneb_Metadata_Treatment_Dose_Inhibitor_Dose")) -head(merged_df) - -# get the number of points that are morphology = 1 and secretome = 1 -counts <- table(merged_df$morphology_ap == 1 & merged_df$secretome_ap == 1) -counts - -# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled -merged_agg <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels, data=merged_df, FUN=mean) -# scatter plot -scatter_compare_treatment <- ( - ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled)) - + geom_point(size=3, alpha=0.5) - + labs(x="Morphology mAP score", y="Secretome mAP score") - + theme_bw() - + ggtitle("Comparison of mAP scores") - + ylim(0,1) - + xlim(0,1) - # Change the legend title - # change the legend shape - + scale_shape_manual( - name="Shuffle type", - labels=c( - "Non-shuffled", - "Shuffled features", - "Shuffled phenotypes" - ), - values=c(19, 17, 15) - ) - + scale_color_manual( - name="Class", - labels=c( - "Control", - "Apoptosis", - "Pyroptosis" - ), - values=c( - brewer.pal(3, "Dark2")[2], - brewer.pal(3, "Dark2")[1], - brewer.pal(3, "Dark2")[3] - ) -) - + figure_theme - # add y = x line - + geom_abline(intercept = 0, slope = 1, linetype="dashed", color = "black") -) -scatter_compare_treatment - -head(merged_agg) - -merged_df <- merged_df %>% - mutate(oneb_Metadata_Treatment_Dose_Inhibitor_Dose = case_when( - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_DMSO_0.025_%' ~ "DMSO 0.1% - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_DMSO_1.000_%' ~ "DMSO 0.1% - DMSO 1.0%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_Z-VAD-FMK_100.000_uM' ~ "DMSO 0.1% - Z-VAD-FMK 100.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_Z-VAD-FMK_30.000_uM' ~ "DMSO 0.1% - Z-VAD-FMK 30.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_DMSO_0.025_%' ~ "Flagellin 1.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM' ~ "Flagellin 1.0 ug/ml - Disulfiram 1.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_0.010_ug_per_ml_DMSO_0.025_%' ~ "LPS 0.01 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_0.100_ug_per_ml_DMSO_0.025_%' ~ "LPS 0.1 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_0.100_ug_per_ml_DMSO_0.0_%' ~ "Flagellin 0.1 ug/ml - DMSO 0.0%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_0.100_ug_per_ml_DMSO_0.025_%' ~ "Flagellin 0.1 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_0.100_uM_DMSO_0.025_%' ~ "Disulfiram 0.1 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - Disulfiram 1.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - Z-VAD-FMK 100.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_1.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 1.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_DMSO_0.0_%' ~ "Flagellin 1.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_1.000_uM_DMSO_0.025_%' ~ "Disulfiram 1.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Thapsigargin_1.000_uM_DMSO_0.025_%' ~ "Thapsigargin 1.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_10.000_nM_DMSO_0.025_%' ~ "Topotecan 10.0 nM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 10.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_0.100_uM' ~ "LPS 10.0 ug/ml - Disulfiram 0.1 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_1.000_uM' ~ "LPS 10.0 ug/ml - Disulfiram 1.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_2.500_uM' ~ "LPS 10.0 ug/ml - Disulfiram 2.5 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM' ~ "LPS 10.0 ug/ml - Z-VAD-FMK 100.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Thapsigargin_10.000_uM_DMSO_0.025_%' ~ "Thapsigargin 10.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_nM_DMSO_0.025_%' ~ "H2O2 100.0 nM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_100.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 100.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_DMSO_0.025_%' ~ "H2O2 100.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_Disulfiram_1.000_uM' ~ "H2O2 100.0 uM - Disulfiram 1.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_Z-VAD-FMK_100.000_uM' ~ "H2O2 100.0 uM - Z-VAD-FMK 100.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_2.500_uM_DMSO_0.025_%' ~ "Disulfiram 2.5 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_20.000_nM_DMSO_0.025_%' ~ "Topotecan 20.0 nM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_5.000_nM_DMSO_0.025_%' ~ "Topotecan 5.0 nM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ "Media ctr 0.0 0", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='media_ctr_0.0_0_Media_0.0_0' ~ "Media ctr 0.0 0" - )) - # replace Media ctr 0.0 0 with Media -merged_df$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- gsub("Media ctr 0.0 0", "Media", merged_df$oneb_Metadata_Treatment_Dose_Inhibitor_Dose) - -# split the oneb_Metadata_Treatment_Dose_Inhibitor_Dose into two columns by the " - " delimiter -merged_df <- merged_df %>% - separate(oneb_Metadata_Treatment_Dose_Inhibitor_Dose, c("inducer", "inhibitor"), sep = " - ", remove = FALSE) - -unique(merged_df$inducer) -# replace the inhibitor NA with Media -merged_df$inhibitor <- ifelse(is.na(merged_df$inhibitor), "Media", merged_df$inhibitor) -unique(merged_df$inhibitor) - -# make the group_treatment column a factor -merged_df$inducer <- factor( - merged_df$inducer, - levels = c( - 'Media', - 'DMSO 0.1%', - - 'Flagellin 0.1 ug/ml', - 'Flagellin 1.0 ug/ml', - - 'LPS 0.01 ug/ml', - 'LPS 0.1 ug/ml', - 'LPS 1.0 ug/ml', - 'LPS 10.0 ug/ml', - 'LPS 100.0 ug/ml', - - 'LPS 1.0 ug/ml + Nigericin 1.0 uM', - 'LPS 1.0 ug/ml + Nigericin 3.0 uM', - 'LPS 1.0 ug/ml + Nigericin 10.0 uM', - - 'LPS 100.0 ug/ml + Nigericin 1.0 uM', - 'LPS 100.0 ug/ml + Nigericin 3.0 uM', - 'LPS 100.0 ug/ml + Nigericin 10.0 uM', - - 'H2O2 100.0 nM', - 'H2O2 100.0 uM', - - 'Disulfiram 0.1 uM', - 'Disulfiram 1.0 uM', - 'Disulfiram 2.5 uM', - - 'Thapsigargin 1.0 uM', - 'Thapsigargin 10.0 uM', - - 'Topotecan 5.0 nM', - 'Topotecan 10.0 nM', - 'Topotecan 20.0 nM' - ) -) - -# make the group_treatment column a factor -merged_df$inhibitor <- factor( - merged_df$inhibitor, - levels = c( - 'Media', - 'DMSO 0.025%', - 'DMSO 1.0%', - - 'Disulfiram 0.1 uM', - 'Disulfiram 1.0 uM', - 'Disulfiram 2.5 uM', - - 'Z-VAD-FMK 30.0 uM', - 'Z-VAD-FMK 100.0 uM' - ) -) -head(merged_df) - -# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled -merged_df <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels + inducer + inhibitor, data=merged_df, FUN=mean) -head(merged_df) - - - -width <- 15 -height <- 15 -options(repr.plot.width=width, repr.plot.height=height) -# scatter plot with fill being the treatment dose -scatter_by_treatment <- ( - ggplot(merged_df, aes(x=morphology_ap, y=secretome_ap, col = inducer, shape=inhibitor)) - + geom_point(size=3, alpha=1) - + labs(x="Morphology mAP score", y="Secretome mAP score") - + theme_bw() - + ggtitle("Comparison of mAP scores") - + ylim(0,1) - + xlim(0,1) - + figure_theme - # Change the legend title - # change the legend shape - + scale_color_manual( - name = "Inducer", - labels = c( - 'Media', - 'DMSO 0.1%', - - 'Flagellin 0.1 ug/ml', - 'Flagellin 1.0 ug/ml', - - 'LPS 0.01 ug/ml', - 'LPS 0.1 ug/ml', - 'LPS 1.0 ug/ml', - 'LPS 10.0 ug/ml', - 'LPS 100.0 ug/ml', - - 'LPS 1.0 ug/ml + Nigericin 1.0 uM', - 'LPS 1.0 ug/ml + Nigericin 3.0 uM', - 'LPS 1.0 ug/ml + Nigericin 10.0 uM', - - 'LPS 100.0 ug/ml + Nigericin 1.0 uM', - 'LPS 100.0 ug/ml + Nigericin 3.0 uM', - 'LPS 100.0 ug/ml + Nigericin 10.0 uM', - - 'H2O2 100.0 nM', - 'H2O2 100.0 uM', - - 'Disulfiram 0.1 uM', - 'Disulfiram 1.0 uM', - 'Disulfiram 2.5 uM', - - 'Thapsigargin 1.0 uM', - 'Thapsigargin 10.0 uM', - - 'Topotecan 5.0 nM', - 'Topotecan 10.0 nM', - 'Topotecan 20.0 nM' - ), - values = colors) - + scale_shape_manual( - name = "Inhibitor", - labels = c( - 'Media', - 'DMSO 0.025%', - 'DMSO 1.0%', - - 'Disulfiram 0.1 uM', - 'Disulfiram 1.0 uM', - 'Disulfiram 2.5 uM', - - 'Z-VAD-FMK 30.0 uM', - 'Z-VAD-FMK 100.0 uM' - - ), - values = shapes - ) - # make the legend 1 column - + guides(color = guide_legend(ncol = 1), shape = guide_legend(ncol = 1)) - + ggplot2::coord_fixed() - + facet_grid(shuffled~.) - # add y = x line - + geom_abline(intercept = 0, slope = 1, linetype = "dashed", color = "black") -) -scatter_by_treatment diff --git a/9.mAP/scripts/run_all_mAPs.sh b/9.mAP/scripts/run_all_mAPs.sh deleted file mode 100644 index 7a6fdd284..000000000 --- a/9.mAP/scripts/run_all_mAPs.sh +++ /dev/null @@ -1,20 +0,0 @@ -#!/bin/bash - -conda activate map - -jupyter nbconvert --to=script --FilesWriter.build_directory=. ../notebooks/*.ipynb - -echo "All notebooks have been converted to scripts." - -echo "Running all mAPs..." - -python 0.generate_map_scores_morphology.py -python 1.aggregate_map_scores_morphology.py -python 2.generate_map_scores_secretome.py -python 3.aggregate_map_scores_secretome.py -python 4.generate_map_scores_morphology_treatment.py -python 5.aggregate_map_scores_morphology_treatment.py -python 6.generate_map_scores_secretome_treatment.py -python 7.aggregate_map_scores_secretome_treatment.py - -echo "All mAPs have been generated and aggregated." diff --git a/9.mAP/src/utils.py b/9.mAP/src/utils.py deleted file mode 100644 index 3e2c7681f..000000000 --- a/9.mAP/src/utils.py +++ /dev/null @@ -1,117 +0,0 @@ -""" -Contains utility functions to import into the analysis - - -`split_data()` was develoepd by @roshankern: -https://github.com/WayScience/mitocheck_data/blob/63f37859d993b8de25fefe1cb8a3aac421c3e08a/utils/load_utils.py#L84 -""" -from typing import Optional - -import numpy as np -import pandas as pd - - -def split_data(pycytominer_output: pd.DataFrame): - """ - split pycytominer output to metadata dataframe and np array of feature values - - Parameters - ---------- - pycytominer_output : pd.DataFrame - dataframe with pycytominer output - - Returns - ------- - pd.Dataframe, np.ndarray - metadata dataframe, feature values - - Credit: - @roshankern: https://github.com/roshankern - """ - all_cols = pycytominer_output.columns.tolist() - metadata_cols = [x for x in all_cols if "Metadata" in x] - - metadata_dataframe = pycytominer_output[metadata_cols] - feature_data = pycytominer_output.drop(metadata_cols, axis=1) - - return metadata_dataframe, feature_data - - -def shuffle_by_labels( - profile: pd.DataFrame, label_col: str, seed: Optional[int] = 1 -) -> pd.DataFrame: - """Shuffles labels in selected column. - - Parameters - ---------- - profile : pd.DataFrame - image-based profile with metadata - target_col : str - selected column that contains the labels - - Returns - ------- - pd.DataFrame - shuffled labeled dataframe - """ - - # type checking - if not isinstance(profile, pd.DataFrame): - raise TypeError(f"`profile` must be a dataframe not {type(profile)}") - if not isinstance(label_col, str): - raise TypeError(f"`label_col` must be a string type not {type(label_col)}") - - # select column and shuffle labels - np.random.seed(seed) - shuffled_labels = np.random.permutation(profile[label_col]) - profile[label_col] = shuffled_labels - - return profile - - -def shuffle_feature_space( - profile: pd.DataFrame, col_idx_split: int, seed=1 -) -> pd.DataFrame: - """Shuffled profile's feature space values - - Parameters - ---------- - feature_val : pd.DataFrame - _description_ - col_idx_split : int - column integer where to split the metadata and extracted features - seed : Optional[int] - seed seeds in order to maintain reproducibility. - - Returns - ------- - pd.DataFrame - feature space shuffled data - """ - - # type checker - if not (profile, pd.DataFrame): - raise TypeError(f"`profile` must be a dataframe not {type(profile)}") - - # select - try: - feature_vals = profile[profile.columns[col_idx_split:]].astype(float) - except Exception: - raise TypeError("The selected index splitter captures non-numerical data") - - # get metadata - metadata = profile[profile.columns[:col_idx_split]] - - # shuffle feature - feature_mat = feature_vals.to_numpy() - for col in feature_mat.T: - np.random.shuffle(col) - - # reconstruct shuffled data - feature_shuffled_data = pd.concat( - [metadata, pd.DataFrame(data=feature_mat)], axis=1 - ) - feature_shuffled_data.columns = profile.columns.tolist() - - # concat metadata with shuffled feature space - return feature_shuffled_data diff --git a/figures/4.figure4/figures/figure4.png b/figures/4.figure4/figures/figure4.png index 133a4a30a..763bd1ba4 100644 Binary files a/figures/4.figure4/figures/figure4.png and b/figures/4.figure4/figures/figure4.png differ diff --git a/figures/4.figure4/figures/filtered_features.png b/figures/4.figure4/figures/filtered_features.png index 77f1f6a6f..2c3655461 100644 Binary files a/figures/4.figure4/figures/filtered_features.png and b/figures/4.figure4/figures/filtered_features.png differ diff --git a/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/global_prediction_trend.png b/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/global_prediction_trend.png index 619937662..f41f0666d 100644 Binary files a/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/global_prediction_trend.png and b/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/global_prediction_trend.png differ diff --git a/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/global_variance_r2.png b/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/global_variance_r2.png index 339455a6f..4df3fa236 100644 Binary files a/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/global_variance_r2.png and b/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/global_variance_r2.png differ diff --git a/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/local_variance_r2.png b/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/local_variance_r2.png index 9781c3ab1..23bc0a304 100644 Binary files a/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/local_variance_r2.png and b/figures/4.figure4/figures/regression/PBMC/aggregated_with_nomic/local_variance_r2.png differ diff --git a/figures/4.figure4/figures/regression/PBMC/top_abs_val_coefficients_enet.pdf b/figures/4.figure4/figures/regression/PBMC/top_abs_val_coefficients_enet.pdf index 520f2e59d..b89d51982 100644 Binary files a/figures/4.figure4/figures/regression/PBMC/top_abs_val_coefficients_enet.pdf and b/figures/4.figure4/figures/regression/PBMC/top_abs_val_coefficients_enet.pdf differ diff --git a/figures/4.figure4/notebooks/figure4.ipynb b/figures/4.figure4/notebooks/figure4.ipynb index 9857059eb..c155adddc 100644 --- a/figures/4.figure4/notebooks/figure4.ipynb +++ b/figures/4.figure4/notebooks/figure4.ipynb @@ -65,11 +65,11 @@ "source": [ "# set the path to the data files\n", "df_stats_path <- file.path(\n", - " paste0(\"../../../6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/\",cell_type,\"/aggregated_with_nomic/model_stats.csv\"\n", + " paste0(\"../../../6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/\",cell_type,\"_aggregated_with_nomic/model_stats.csv\"\n", " )\n", " )\n", "df_variance_path <- file.path(\n", - " paste0(\"../../../6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/\",cell_type,\"/aggregated_with_nomic/variance_r2_stats.csv\"\n", + " paste0(\"../../../6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/\",cell_type,\"_aggregated_with_nomic/variance_r2_stats.csv\"\n", " )\n", ")\n", "\n", @@ -99,212 +99,64 @@ "data": { "text/html": [ "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 14
explained_varianceneg_mean_absolute_errorneg_mean_squared_errorwelltreatmentr2cytokinedata_splitshufflepredicted_valueactual_valuelog10_neg_mean_absolute_errorlog10_neg_mean_squared_errorlog10_explained_variance
<dbl><dbl><dbl><chr><chr><dbl><chr><chr><chr><dbl><dbl><dbl><dbl><dbl>
11-0.12876296-0.016579900B05LPS_Nigericin_100.000_1.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.62261460.89020901.78041810
21-0.09606601-0.009228678B08LPS_0.010_DMSO_0.025 0GFbetatrain_datafinal0.49691740.40313871.01743022.03486050
31-0.21557860-0.046474132B10LPS_Nigericin_100.000_1.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.70736320.66639441.33278870
41-0.57668367-0.332564053C02LPS_0.100_DMSO_0.025 0GFbetatrain_datafinal0.49691740.16192330.23906230.47812470
51-0.11961401-0.014307512C05LPS_Nigericin_100.000_3.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.61368350.92221791.84443590
61-0.31175502-0.097191194C06DMSO_0.100_DMSO_0.025 0GFbetatrain_datafinal0.49691740.19258510.50618651.01237310
\n" - ], - "text/latex": [ - "A data.frame: 6 × 14\n", - "\\begin{tabular}{r|llllllllllllll}\n", - " & explained\\_variance & neg\\_mean\\_absolute\\_error & neg\\_mean\\_squared\\_error & well & treatment & r2 & cytokine & data\\_split & shuffle & predicted\\_value & actual\\_value & log10\\_neg\\_mean\\_absolute\\_error & log10\\_neg\\_mean\\_squared\\_error & log10\\_explained\\_variance\\\\\n", - " & & & & & & & & & & & & & & \\\\\n", - "\\hline\n", - "\t1 & 1 & -0.12876296 & -0.016579900 & B05 & LPS\\_Nigericin\\_100.000\\_1.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.6226146 & 0.8902090 & 1.7804181 & 0\\\\\n", - "\t2 & 1 & -0.09606601 & -0.009228678 & B08 & LPS\\_0.010\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.4031387 & 1.0174302 & 2.0348605 & 0\\\\\n", - "\t3 & 1 & -0.21557860 & -0.046474132 & B10 & LPS\\_Nigericin\\_100.000\\_1.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.7073632 & 0.6663944 & 1.3327887 & 0\\\\\n", - "\t4 & 1 & -0.57668367 & -0.332564053 & C02 & LPS\\_0.100\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.1619233 & 0.2390623 & 0.4781247 & 0\\\\\n", - "\t5 & 1 & -0.11961401 & -0.014307512 & C05 & LPS\\_Nigericin\\_100.000\\_3.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.6136835 & 0.9222179 & 1.8444359 & 0\\\\\n", - "\t6 & 1 & -0.31175502 & -0.097191194 & C06 & DMSO\\_0.100\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.1925851 & 0.5061865 & 1.0123731 & 0\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 14\n", - "\n", - "| | explained_variance <dbl> | neg_mean_absolute_error <dbl> | neg_mean_squared_error <dbl> | well <chr> | treatment <chr> | r2 <dbl> | cytokine <chr> | data_split <chr> | shuffle <chr> | predicted_value <dbl> | actual_value <dbl> | log10_neg_mean_absolute_error <dbl> | log10_neg_mean_squared_error <dbl> | log10_explained_variance <dbl> |\n", - "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", - "| 1 | 1 | -0.12876296 | -0.016579900 | B05 | LPS_Nigericin_100.000_1.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.6226146 | 0.8902090 | 1.7804181 | 0 |\n", - "| 2 | 1 | -0.09606601 | -0.009228678 | B08 | LPS_0.010_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.4031387 | 1.0174302 | 2.0348605 | 0 |\n", - "| 3 | 1 | -0.21557860 | -0.046474132 | B10 | LPS_Nigericin_100.000_1.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.7073632 | 0.6663944 | 1.3327887 | 0 |\n", - "| 4 | 1 | -0.57668367 | -0.332564053 | C02 | LPS_0.100_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.1619233 | 0.2390623 | 0.4781247 | 0 |\n", - "| 5 | 1 | -0.11961401 | -0.014307512 | C05 | LPS_Nigericin_100.000_3.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.6136835 | 0.9222179 | 1.8444359 | 0 |\n", - "| 6 | 1 | -0.31175502 | -0.097191194 | C06 | DMSO_0.100_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.1925851 | 0.5061865 | 1.0123731 | 0 |\n", - "\n" - ], - "text/plain": [ - " explained_variance neg_mean_absolute_error neg_mean_squared_error well\n", - "1 1 -0.12876296 -0.016579900 B05 \n", - "2 1 -0.09606601 -0.009228678 B08 \n", - "3 1 -0.21557860 -0.046474132 B10 \n", - "4 1 -0.57668367 -0.332564053 C02 \n", - "5 1 -0.11961401 -0.014307512 C05 \n", - "6 1 -0.31175502 -0.097191194 C06 \n", - " treatment r2 cytokine data_split shuffle\n", - "1 LPS_Nigericin_100.000_1.0_DMSO_0.025 0 GFbeta train_data final \n", - "2 LPS_0.010_DMSO_0.025 0 GFbeta train_data final \n", - "3 LPS_Nigericin_100.000_1.0_DMSO_0.025 0 GFbeta train_data final \n", - "4 LPS_0.100_DMSO_0.025 0 GFbeta train_data final \n", - "5 LPS_Nigericin_100.000_3.0_DMSO_0.025 0 GFbeta train_data final \n", - "6 DMSO_0.100_DMSO_0.025 0 GFbeta train_data final \n", - " predicted_value actual_value log10_neg_mean_absolute_error\n", - "1 0.4969174 0.6226146 0.8902090 \n", - "2 0.4969174 0.4031387 1.0174302 \n", - "3 0.4969174 0.7073632 0.6663944 \n", - "4 0.4969174 0.1619233 0.2390623 \n", - "5 0.4969174 0.6136835 0.9222179 \n", - "6 0.4969174 0.1925851 0.5061865 \n", - " log10_neg_mean_squared_error log10_explained_variance\n", - "1 1.7804181 0 \n", - "2 2.0348605 0 \n", - "3 1.3327887 0 \n", - "4 0.4781247 0 \n", - "5 1.8444359 0 \n", - "6 1.0123731 0 " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 6
cytokinedata_splitshufflepredicted_valueactual_valuer2
<chr><chr><chr><dbl><dbl><chr>
1XCL1(Lymphotactin)test_data final 0.0204805040.02890534[0.65955376]
2XCL1(Lymphotactin)train_datafinal 0.0192161610.03922649[0.59506056]
3FGF-19 test_data shuffled_baseline0.0115749920.04871310[-0.12988404]
4FGF-19 train_datashuffled_baseline0.0130186790.02982844[-0.81728511]
5IF-epsilon test_data final 0.0062430450.03106936[0.13484578]
6IF-epsilon train_datafinal 0.0070305690.03819321[0.31434654]
\n" - ], - "text/latex": [ - "A data.frame: 6 × 6\n", - "\\begin{tabular}{r|llllll}\n", - " & cytokine & data\\_split & shuffle & predicted\\_value & actual\\_value & r2\\\\\n", - " & & & & & & \\\\\n", - "\\hline\n", - "\t1 & XCL1(Lymphotactin) & test\\_data & final & 0.020480504 & 0.02890534 & {[}0.65955376{]} \\\\\n", - "\t2 & XCL1(Lymphotactin) & train\\_data & final & 0.019216161 & 0.03922649 & {[}0.59506056{]} \\\\\n", - "\t3 & FGF-19 & test\\_data & shuffled\\_baseline & 0.011574992 & 0.04871310 & {[}-0.12988404{]}\\\\\n", - "\t4 & FGF-19 & train\\_data & shuffled\\_baseline & 0.013018679 & 0.02982844 & {[}-0.81728511{]}\\\\\n", - "\t5 & IF-epsilon & test\\_data & final & 0.006243045 & 0.03106936 & {[}0.13484578{]} \\\\\n", - "\t6 & IF-epsilon & train\\_data & final & 0.007030569 & 0.03819321 & {[}0.31434654{]} \\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 6\n", - "\n", - "| | cytokine <chr> | data_split <chr> | shuffle <chr> | predicted_value <dbl> | actual_value <dbl> | r2 <chr> |\n", - "|---|---|---|---|---|---|---|\n", - "| 1 | XCL1(Lymphotactin) | test_data | final | 0.020480504 | 0.02890534 | [0.65955376] |\n", - "| 2 | XCL1(Lymphotactin) | train_data | final | 0.019216161 | 0.03922649 | [0.59506056] |\n", - "| 3 | FGF-19 | test_data | shuffled_baseline | 0.011574992 | 0.04871310 | [-0.12988404] |\n", - "| 4 | FGF-19 | train_data | shuffled_baseline | 0.013018679 | 0.02982844 | [-0.81728511] |\n", - "| 5 | IF-epsilon | test_data | final | 0.006243045 | 0.03106936 | [0.13484578] |\n", - "| 6 | IF-epsilon | train_data | final | 0.007030569 | 0.03819321 | [0.31434654] |\n", - "\n" - ], - "text/plain": [ - " cytokine data_split shuffle predicted_value actual_value\n", - "1 XCL1(Lymphotactin) test_data final 0.020480504 0.02890534 \n", - "2 XCL1(Lymphotactin) train_data final 0.019216161 0.03922649 \n", - "3 FGF-19 test_data shuffled_baseline 0.011574992 0.04871310 \n", - "4 FGF-19 train_data shuffled_baseline 0.013018679 0.02982844 \n", - "5 IF-epsilon test_data final 0.006243045 0.03106936 \n", - "6 IF-epsilon train_data final 0.007030569 0.03819321 \n", - " r2 \n", - "1 [0.65955376] \n", - "2 [0.59506056] \n", - "3 [-0.12988404]\n", - "4 [-0.81728511]\n", - "5 [0.13484578] \n", - "6 [0.31434654] " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", + "\n", "\n", "\t\n", "\t\n", "\n", "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", "\n", "
A data.frame: 6 × 6A data.frame: 6 \u00d7 6
cytokinedata_splitshufflepredicted_valueactual_valuer2
<chr><chr><chr><dbl><dbl><dbl>
1XCL1(Lymphotactin)test_data final 0.0204805040.02890534 0.6595538
2XCL1(Lymphotactin)train_datafinal 0.0192161610.03922649 0.5950606
3FGF-19 test_data shuffled_baseline0.0115749920.04871310-0.1298840
4FGF-19 train_datashuffled_baseline0.0130186790.02982844-0.8172851
5IF-epsilon test_data final 0.0062430450.03106936 0.1348458
6IF-epsilon train_datafinal 0.0070305690.03819321 0.3143465
1VEGFReceptor2(Flk-1)test_data final 7.754802e-050.02709775-0.03082779
2VEGFReceptor2(Flk-1)train_datafinal 9.281482e-050.02369869 0.01144109
3CCL28 test_data shuffled_baseline1.646352e-030.04206825-0.01450459
4CCL28 train_datashuffled_baseline1.475837e-030.02633373 0.00128010
5TFRI test_data final 1.834369e-030.02387115 0.07520071
6TFRI train_datafinal 1.715017e-030.03261339 0.09234197
\n" ], "text/latex": [ - "A data.frame: 6 × 6\n", + "A data.frame: 6 \u00d7 6\n", "\\begin{tabular}{r|llllll}\n", " & cytokine & data\\_split & shuffle & predicted\\_value & actual\\_value & r2\\\\\n", " & & & & & & \\\\\n", "\\hline\n", - "\t1 & XCL1(Lymphotactin) & test\\_data & final & 0.020480504 & 0.02890534 & 0.6595538\\\\\n", - "\t2 & XCL1(Lymphotactin) & train\\_data & final & 0.019216161 & 0.03922649 & 0.5950606\\\\\n", - "\t3 & FGF-19 & test\\_data & shuffled\\_baseline & 0.011574992 & 0.04871310 & -0.1298840\\\\\n", - "\t4 & FGF-19 & train\\_data & shuffled\\_baseline & 0.013018679 & 0.02982844 & -0.8172851\\\\\n", - "\t5 & IF-epsilon & test\\_data & final & 0.006243045 & 0.03106936 & 0.1348458\\\\\n", - "\t6 & IF-epsilon & train\\_data & final & 0.007030569 & 0.03819321 & 0.3143465\\\\\n", + "\t1 & VEGFReceptor2(Flk-1) & test\\_data & final & 7.754802e-05 & 0.02709775 & -0.03082779\\\\\n", + "\t2 & VEGFReceptor2(Flk-1) & train\\_data & final & 9.281482e-05 & 0.02369869 & 0.01144109\\\\\n", + "\t3 & CCL28 & test\\_data & shuffled\\_baseline & 1.646352e-03 & 0.04206825 & -0.01450459\\\\\n", + "\t4 & CCL28 & train\\_data & shuffled\\_baseline & 1.475837e-03 & 0.02633373 & 0.00128010\\\\\n", + "\t5 & TFRI & test\\_data & final & 1.834369e-03 & 0.02387115 & 0.07520071\\\\\n", + "\t6 & TFRI & train\\_data & final & 1.715017e-03 & 0.03261339 & 0.09234197\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", - "A data.frame: 6 × 6\n", + "A data.frame: 6 \u00d7 6\n", "\n", "| | cytokine <chr> | data_split <chr> | shuffle <chr> | predicted_value <dbl> | actual_value <dbl> | r2 <dbl> |\n", "|---|---|---|---|---|---|---|\n", - "| 1 | XCL1(Lymphotactin) | test_data | final | 0.020480504 | 0.02890534 | 0.6595538 |\n", - "| 2 | XCL1(Lymphotactin) | train_data | final | 0.019216161 | 0.03922649 | 0.5950606 |\n", - "| 3 | FGF-19 | test_data | shuffled_baseline | 0.011574992 | 0.04871310 | -0.1298840 |\n", - "| 4 | FGF-19 | train_data | shuffled_baseline | 0.013018679 | 0.02982844 | -0.8172851 |\n", - "| 5 | IF-epsilon | test_data | final | 0.006243045 | 0.03106936 | 0.1348458 |\n", - "| 6 | IF-epsilon | train_data | final | 0.007030569 | 0.03819321 | 0.3143465 |\n", + "| 1 | VEGFReceptor2(Flk-1) | test_data | final | 7.754802e-05 | 0.02709775 | -0.03082779 |\n", + "| 2 | VEGFReceptor2(Flk-1) | train_data | final | 9.281482e-05 | 0.02369869 | 0.01144109 |\n", + "| 3 | CCL28 | test_data | shuffled_baseline | 1.646352e-03 | 0.04206825 | -0.01450459 |\n", + "| 4 | CCL28 | train_data | shuffled_baseline | 1.475837e-03 | 0.02633373 | 0.00128010 |\n", + "| 5 | TFRI | test_data | final | 1.834369e-03 | 0.02387115 | 0.07520071 |\n", + "| 6 | TFRI | train_data | final | 1.715017e-03 | 0.03261339 | 0.09234197 |\n", "\n" ], "text/plain": [ - " cytokine data_split shuffle predicted_value actual_value\n", - "1 XCL1(Lymphotactin) test_data final 0.020480504 0.02890534 \n", - "2 XCL1(Lymphotactin) train_data final 0.019216161 0.03922649 \n", - "3 FGF-19 test_data shuffled_baseline 0.011574992 0.04871310 \n", - "4 FGF-19 train_data shuffled_baseline 0.013018679 0.02982844 \n", - "5 IF-epsilon test_data final 0.006243045 0.03106936 \n", - "6 IF-epsilon train_data final 0.007030569 0.03819321 \n", - " r2 \n", - "1 0.6595538\n", - "2 0.5950606\n", - "3 -0.1298840\n", - "4 -0.8172851\n", - "5 0.1348458\n", - "6 0.3143465" + " cytokine data_split shuffle predicted_value\n", + "1 VEGFReceptor2(Flk-1) test_data final 7.754802e-05 \n", + "2 VEGFReceptor2(Flk-1) train_data final 9.281482e-05 \n", + "3 CCL28 test_data shuffled_baseline 1.646352e-03 \n", + "4 CCL28 train_data shuffled_baseline 1.475837e-03 \n", + "5 TFRI test_data final 1.834369e-03 \n", + "6 TFRI train_data final 1.715017e-03 \n", + " actual_value r2 \n", + "1 0.02709775 -0.03082779\n", + "2 0.02369869 0.01144109\n", + "3 0.04206825 -0.01450459\n", + "4 0.02633373 0.00128010\n", + "5 0.02387115 0.07520071\n", + "6 0.03261339 0.09234197" ] }, "metadata": {}, @@ -312,8 +164,6 @@ } ], "source": [ - "head(df_stats)\n", - "head(df_variance)\n", "# remove '[]' from the string in the column\n", "df_variance$r2 <- gsub(\"\\\\[|\\\\]\", \"\", df_variance$r2)\n", "# set the column as numeric\n", @@ -348,7 +198,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -406,21 +256,21 @@ "output_type": "stream", "text": [ "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 610 rows containing missing values or values outside the scale range\n", - "(`geom_point()`).”\n", + "\u201c\u001b[1m\u001b[22mRemoved 309 rows containing missing values or values outside the scale range\n", + "(`geom_point()`).\u201d\n", "Warning message in get_plot_component(plot, \"guide-box\"):\n", - "“Multiple components found; returning the first one. To return all, use `return_all = TRUE`.”\n", + "\u201cMultiple components found; returning the first one. To return all, use `return_all = TRUE`.\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 610 rows containing missing values or values outside the scale range\n", - "(`geom_point()`).”\n", + "\u201c\u001b[1m\u001b[22mRemoved 309 rows containing missing values or values outside the scale range\n", + "(`geom_point()`).\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 610 rows containing missing values or values outside the scale range\n", - "(`geom_point()`).”\n" + "\u201c\u001b[1m\u001b[22mRemoved 309 rows containing missing values or values outside the scale range\n", + "(`geom_point()`).\u201d\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -499,7 +349,7 @@ "df_stats$shuffle_plus_data_split <- gsub(\"final_test_data\", \"Final (Test)\", df_stats$shuffle_plus_data_split)\n", "df_stats$shuffle_plus_data_split <- gsub(\"final_train_data\", \"Final (Train)\", df_stats$shuffle_plus_data_split)\n", "df_stats$shuffle_plus_data_split <- gsub(\"shuffled_baseline_test_data\", \"Shuffled (Test)\", df_stats$shuffle_plus_data_split)\n", - "df_stats$shuffle_plus_data_split <- gsub(\"shuffled_baseline_train_data\", \"Shuffled (Train)\", df_stats$shuffle_plus_data_split)\n" + "df_stats$shuffle_plus_data_split <- gsub(\"shuffled_baseline_train_data\", \"Shuffled (Train)\", df_stats$shuffle_plus_data_split)" ] }, { @@ -516,21 +366,21 @@ "output_type": "stream", "text": [ "Warning message:\n", - "“\u001b[1m\u001b[22mUsing `size` aesthetic for lines was deprecated in ggplot2 3.4.0.\n", - "\u001b[36mℹ\u001b[39m Please use `linewidth` instead.”\n", + "\u201c\u001b[1m\u001b[22mUsing `size` aesthetic for lines was deprecated in ggplot2 3.4.0.\n", + "\u001b[36m\u2139\u001b[39m Please use `linewidth` instead.\u201d\n", "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 478 rows containing non-finite outside the scale range\n", - "(`stat_smooth()`).”\n", + "\u201c\u001b[1m\u001b[22mRemoved 439 rows containing non-finite outside the scale range\n", + "(`stat_smooth()`).\u201d\n", "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 478 rows containing non-finite outside the scale range\n", - "(`stat_smooth()`).”\n" + "\u201c\u001b[1m\u001b[22mRemoved 439 rows containing non-finite outside the scale range\n", + "(`stat_smooth()`).\u201d\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -545,7 +395,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -648,28 +498,50 @@ "languageId": "r" } }, + "outputs": [], + "source": [ + "# df_stats factor levels\n", + "df_stats$shuffle_plus_data_split <- factor(\n", + " df_stats$shuffle_plus_data_split,\n", + " levels = c(\n", + " \"Final (Train)\",\n", + " \"Final (Test)\",\n", + " \"Shuffled (Train)\",\n", + " \"Shuffled (Test)\"\n", + " )\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "vscode": { + "languageId": "r" + } + }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 26 rows containing non-finite outside the scale range\n", - "(`stat_smooth()`).”\n", + "\u201c\u001b[1m\u001b[22mRemoved 30 rows containing non-finite outside the scale range\n", + "(`stat_smooth()`).\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 26 rows containing missing values or values outside the scale range\n", - "(`geom_point()`).”\n", + "\u201c\u001b[1m\u001b[22mRemoved 30 rows containing missing values or values outside the scale range\n", + "(`geom_point()`).\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 28 rows containing non-finite outside the scale range\n", - "(`stat_smooth()`).”\n", + "\u201c\u001b[1m\u001b[22mRemoved 27 rows containing non-finite outside the scale range\n", + "(`stat_smooth()`).\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 28 rows containing missing values or values outside the scale range\n", - "(`geom_point()`).”\n" + "\u201c\u001b[1m\u001b[22mRemoved 27 rows containing missing values or values outside the scale range\n", + "(`geom_point()`).\u201d\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -684,7 +556,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -699,16 +571,6 @@ } ], "source": [ - "# df_stats factor levels\n", - "df_stats$shuffle_plus_data_split <- factor(\n", - " df_stats$shuffle_plus_data_split,\n", - " levels = c(\n", - " \"Final (Train)\",\n", - " \"Final (Test)\",\n", - " \"Shuffled (Train)\",\n", - " \"Shuffled (Test)\"\n", - " )\n", - ")\n", "\n", "enet_cp_fig <- file.path(paste0(enet_cp_fig_path,\"Predicted_vs_Actual_all_cytokines.png\"))\n", "# set plot size\n", @@ -733,7 +595,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": { "vscode": { "languageId": "r" @@ -753,29 +615,13 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": { "vscode": { "languageId": "r" } }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 360, - "width": 360 - } - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# per cytokine graph\n", "file_path <- file.path(paste0(enet_cp_fig_path))\n", @@ -799,32 +645,12 @@ "# split the log10_neg_mean_absolute_error column into two columns\n", "tmp_df <- cbind(tmp_df, tmp_df$mean_log10_neg_mean_absolute_error)\n", "# drop the log10_neg_mean_absolute_error column by name\n", - "tmp_df <- tmp_df[, !names(tmp_df) %in% c('mean_log10_neg_mean_absolute_error')]\n", - "# split the mean_log10_neg_mean_absolute_error column into two columns\n", - "\n", - "model_performance_il1b <- (\n", - " ggplot(tmp_df, aes(x=data_split, y=mean, fill=shuffle)) \n", - " + geom_bar(stat=\"identity\", position=position_dodge()) \n", - " + geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd), width=.2, position=position_dodge(.9)) \n", - " + labs(x=\"Data Split\", y=\"log10_neg_mean_absolute_error\") \n", - " + ggtitle(cytokine)\n", - " + theme_bw()\n", - " + figure_theme\n", - " + ylab(\"-log10(MSE)\")\n", - ")\n", - "model_performance_il1b\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Boxplot" + "tmp_df <- tmp_df[, !names(tmp_df) %in% c('mean_log10_neg_mean_absolute_error')]\n" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": { "vscode": { "languageId": "r" @@ -833,93 +659,45 @@ "outputs": [ { "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 15
explained_varianceneg_mean_absolute_errorneg_mean_squared_errorwelltreatmentr2cytokinedata_splitshufflepredicted_valueactual_valuelog10_neg_mean_absolute_errorlog10_neg_mean_squared_errorlog10_explained_varianceshuffle_plus_data_split
<dbl><dbl><dbl><chr><chr><dbl><chr><chr><chr><dbl><dbl><dbl><dbl><dbl><fct>
11-0.12876296-0.016579900B05LPS_Nigericin_100.000_1.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.62261460.89020901.78041810Final (Train)
21-0.09606601-0.009228678B08LPS_0.010_DMSO_0.025 0GFbetatrain_datafinal0.49691740.40313871.01743022.03486050Final (Train)
31-0.21557860-0.046474132B10LPS_Nigericin_100.000_1.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.70736320.66639441.33278870Final (Train)
41-0.57668367-0.332564053C02LPS_0.100_DMSO_0.025 0GFbetatrain_datafinal0.49691740.16192330.23906230.47812470Final (Train)
51-0.11961401-0.014307512C05LPS_Nigericin_100.000_3.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.61368350.92221791.84443590Final (Train)
61-0.31175502-0.097191194C06DMSO_0.100_DMSO_0.025 0GFbetatrain_datafinal0.49691740.19258510.50618651.01237310Final (Train)
\n" - ], - "text/latex": [ - "A data.frame: 6 × 15\n", - "\\begin{tabular}{r|lllllllllllllll}\n", - " & explained\\_variance & neg\\_mean\\_absolute\\_error & neg\\_mean\\_squared\\_error & well & treatment & r2 & cytokine & data\\_split & shuffle & predicted\\_value & actual\\_value & log10\\_neg\\_mean\\_absolute\\_error & log10\\_neg\\_mean\\_squared\\_error & log10\\_explained\\_variance & shuffle\\_plus\\_data\\_split\\\\\n", - " & & & & & & & & & & & & & & & \\\\\n", - "\\hline\n", - "\t1 & 1 & -0.12876296 & -0.016579900 & B05 & LPS\\_Nigericin\\_100.000\\_1.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.6226146 & 0.8902090 & 1.7804181 & 0 & Final (Train)\\\\\n", - "\t2 & 1 & -0.09606601 & -0.009228678 & B08 & LPS\\_0.010\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.4031387 & 1.0174302 & 2.0348605 & 0 & Final (Train)\\\\\n", - "\t3 & 1 & -0.21557860 & -0.046474132 & B10 & LPS\\_Nigericin\\_100.000\\_1.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.7073632 & 0.6663944 & 1.3327887 & 0 & Final (Train)\\\\\n", - "\t4 & 1 & -0.57668367 & -0.332564053 & C02 & LPS\\_0.100\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.1619233 & 0.2390623 & 0.4781247 & 0 & Final (Train)\\\\\n", - "\t5 & 1 & -0.11961401 & -0.014307512 & C05 & LPS\\_Nigericin\\_100.000\\_3.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.6136835 & 0.9222179 & 1.8444359 & 0 & Final (Train)\\\\\n", - "\t6 & 1 & -0.31175502 & -0.097191194 & C06 & DMSO\\_0.100\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.1925851 & 0.5061865 & 1.0123731 & 0 & Final (Train)\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 15\n", - "\n", - "| | explained_variance <dbl> | neg_mean_absolute_error <dbl> | neg_mean_squared_error <dbl> | well <chr> | treatment <chr> | r2 <dbl> | cytokine <chr> | data_split <chr> | shuffle <chr> | predicted_value <dbl> | actual_value <dbl> | log10_neg_mean_absolute_error <dbl> | log10_neg_mean_squared_error <dbl> | log10_explained_variance <dbl> | shuffle_plus_data_split <fct> |\n", - "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", - "| 1 | 1 | -0.12876296 | -0.016579900 | B05 | LPS_Nigericin_100.000_1.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.6226146 | 0.8902090 | 1.7804181 | 0 | Final (Train) |\n", - "| 2 | 1 | -0.09606601 | -0.009228678 | B08 | LPS_0.010_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.4031387 | 1.0174302 | 2.0348605 | 0 | Final (Train) |\n", - "| 3 | 1 | -0.21557860 | -0.046474132 | B10 | LPS_Nigericin_100.000_1.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.7073632 | 0.6663944 | 1.3327887 | 0 | Final (Train) |\n", - "| 4 | 1 | -0.57668367 | -0.332564053 | C02 | LPS_0.100_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.1619233 | 0.2390623 | 0.4781247 | 0 | Final (Train) |\n", - "| 5 | 1 | -0.11961401 | -0.014307512 | C05 | LPS_Nigericin_100.000_3.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.6136835 | 0.9222179 | 1.8444359 | 0 | Final (Train) |\n", - "| 6 | 1 | -0.31175502 | -0.097191194 | C06 | DMSO_0.100_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.1925851 | 0.5061865 | 1.0123731 | 0 | Final (Train) |\n", - "\n" - ], + "image/png": "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", "text/plain": [ - " explained_variance neg_mean_absolute_error neg_mean_squared_error well\n", - "1 1 -0.12876296 -0.016579900 B05 \n", - "2 1 -0.09606601 -0.009228678 B08 \n", - "3 1 -0.21557860 -0.046474132 B10 \n", - "4 1 -0.57668367 -0.332564053 C02 \n", - "5 1 -0.11961401 -0.014307512 C05 \n", - "6 1 -0.31175502 -0.097191194 C06 \n", - " treatment r2 cytokine data_split shuffle\n", - "1 LPS_Nigericin_100.000_1.0_DMSO_0.025 0 GFbeta train_data final \n", - "2 LPS_0.010_DMSO_0.025 0 GFbeta train_data final \n", - "3 LPS_Nigericin_100.000_1.0_DMSO_0.025 0 GFbeta train_data final \n", - "4 LPS_0.100_DMSO_0.025 0 GFbeta train_data final \n", - "5 LPS_Nigericin_100.000_3.0_DMSO_0.025 0 GFbeta train_data final \n", - "6 DMSO_0.100_DMSO_0.025 0 GFbeta train_data final \n", - " predicted_value actual_value log10_neg_mean_absolute_error\n", - "1 0.4969174 0.6226146 0.8902090 \n", - "2 0.4969174 0.4031387 1.0174302 \n", - "3 0.4969174 0.7073632 0.6663944 \n", - "4 0.4969174 0.1619233 0.2390623 \n", - "5 0.4969174 0.6136835 0.9222179 \n", - "6 0.4969174 0.1925851 0.5061865 \n", - " log10_neg_mean_squared_error log10_explained_variance shuffle_plus_data_split\n", - "1 1.7804181 0 Final (Train) \n", - "2 2.0348605 0 Final (Train) \n", - "3 1.3327887 0 Final (Train) \n", - "4 0.4781247 0 Final (Train) \n", - "5 1.8444359 0 Final (Train) \n", - "6 1.0123731 0 Final (Train) " + "plot without title" ] }, - "metadata": {}, + "metadata": { + "image/png": { + "height": 360, + "width": 360 + } + }, "output_type": "display_data" } ], "source": [ - "head(df_stats)" + "\n", + "model_performance_il1b <- (\n", + " ggplot(tmp_df, aes(x=data_split, y=mean, fill=shuffle)) \n", + " + geom_bar(stat=\"identity\", position=position_dodge()) \n", + " + geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd), width=.2, position=position_dodge(.9)) \n", + " + labs(x=\"Data Split\", y=\"log10_neg_mean_absolute_error\") \n", + " + ggtitle(cytokine)\n", + " + theme_bw()\n", + " + figure_theme\n", + " + ylab(\"-log10(MSE)\")\n", + ")\n", + "model_performance_il1b\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Boxplot" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": { "vscode": { "languageId": "r" @@ -930,78 +708,78 @@ "data": { "text/html": [ "\n", - "\n", + "\n", "\n", - "\t\n", + "\t\n", "\t\n", "\n", "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", "\n", "
A data.frame: 6 × 15A data.frame: 6 \u00d7 15
explained_varianceneg_mean_absolute_errorneg_mean_squared_errorwelltreatmentr2cytokinedata_splitshufflepredicted_valueactual_valuelog10_neg_mean_absolute_errorlog10_neg_mean_squared_errorlog10_explained_varianceshuffle_plus_data_split
explained_varianceneg_mean_absolute_errorneg_mean_squared_errortreatmentwellr2cytokinedata_splitshufflepredicted_valueactual_valuelog10_neg_mean_absolute_errorlog10_neg_mean_squared_errorlog10_explained_varianceshuffle_plus_data_split
<dbl><dbl><dbl><chr><chr><dbl><chr><chr><chr><dbl><dbl><dbl><dbl><dbl><fct>
11-0.12876296-0.016579900B05LPS_Nigericin_100.000_1.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.62261460.89020901.78041810Final (Train)
21-0.09606601-0.009228678B08LPS_0.010_DMSO_0.025 0GFbetatrain_datafinal0.49691740.40313871.01743022.03486050Final (Train)
31-0.21557860-0.046474132B10LPS_Nigericin_100.000_1.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.70736320.66639441.33278870Final (Train)
41-0.57668367-0.332564053C02LPS_0.100_DMSO_0.025 0GFbetatrain_datafinal0.49691740.16192330.23906230.47812470Final (Train)
51-0.11961401-0.014307512C05LPS_Nigericin_100.000_3.0_DMSO_0.0250GFbetatrain_datafinal0.49691740.61368350.92221791.84443590Final (Train)
61-0.31175502-0.097191194C06DMSO_0.100_DMSO_0.025 0GFbetatrain_datafinal0.49691740.19258510.50618651.01237310Final (Train)
10.5255427-0.01121794-0.01121794DMSO_0.100_%_DMSO_0.025_% B070.5255427FA-Ltrain_datafinal0.65094440.60110401.9500871.9500870.279392Final (Train)
20.5255427-0.01121794-0.01121794LPS_0.010_ug_per_ml_DMSO_0.025_% B080.5255427FA-Ltrain_datafinal0.66929930.64349431.9500871.9500870.279392Final (Train)
30.5255427-0.01121794-0.01121794LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%B100.5255427FA-Ltrain_datafinal0.56399840.53413211.9500871.9500870.279392Final (Train)
40.5255427-0.01121794-0.01121794LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%B110.5255427FA-Ltrain_datafinal0.58980940.71695791.9500871.9500870.279392Final (Train)
50.5255427-0.01121794-0.01121794Media B120.5255427FA-Ltrain_datafinal0.63300560.56869431.9500871.9500870.279392Final (Train)
60.5255427-0.01121794-0.01121794LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%C040.5255427FA-Ltrain_datafinal0.43635070.65152271.9500871.9500870.279392Final (Train)
\n" ], "text/latex": [ - "A data.frame: 6 × 15\n", + "A data.frame: 6 \u00d7 15\n", "\\begin{tabular}{r|lllllllllllllll}\n", - " & explained\\_variance & neg\\_mean\\_absolute\\_error & neg\\_mean\\_squared\\_error & well & treatment & r2 & cytokine & data\\_split & shuffle & predicted\\_value & actual\\_value & log10\\_neg\\_mean\\_absolute\\_error & log10\\_neg\\_mean\\_squared\\_error & log10\\_explained\\_variance & shuffle\\_plus\\_data\\_split\\\\\n", + " & explained\\_variance & neg\\_mean\\_absolute\\_error & neg\\_mean\\_squared\\_error & treatment & well & r2 & cytokine & data\\_split & shuffle & predicted\\_value & actual\\_value & log10\\_neg\\_mean\\_absolute\\_error & log10\\_neg\\_mean\\_squared\\_error & log10\\_explained\\_variance & shuffle\\_plus\\_data\\_split\\\\\n", " & & & & & & & & & & & & & & & \\\\\n", "\\hline\n", - "\t1 & 1 & -0.12876296 & -0.016579900 & B05 & LPS\\_Nigericin\\_100.000\\_1.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.6226146 & 0.8902090 & 1.7804181 & 0 & Final (Train)\\\\\n", - "\t2 & 1 & -0.09606601 & -0.009228678 & B08 & LPS\\_0.010\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.4031387 & 1.0174302 & 2.0348605 & 0 & Final (Train)\\\\\n", - "\t3 & 1 & -0.21557860 & -0.046474132 & B10 & LPS\\_Nigericin\\_100.000\\_1.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.7073632 & 0.6663944 & 1.3327887 & 0 & Final (Train)\\\\\n", - "\t4 & 1 & -0.57668367 & -0.332564053 & C02 & LPS\\_0.100\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.1619233 & 0.2390623 & 0.4781247 & 0 & Final (Train)\\\\\n", - "\t5 & 1 & -0.11961401 & -0.014307512 & C05 & LPS\\_Nigericin\\_100.000\\_3.0\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.6136835 & 0.9222179 & 1.8444359 & 0 & Final (Train)\\\\\n", - "\t6 & 1 & -0.31175502 & -0.097191194 & C06 & DMSO\\_0.100\\_DMSO\\_0.025 & 0 & GFbeta & train\\_data & final & 0.4969174 & 0.1925851 & 0.5061865 & 1.0123731 & 0 & Final (Train)\\\\\n", + "\t1 & 0.5255427 & -0.01121794 & -0.01121794 & DMSO\\_0.100\\_\\%\\_DMSO\\_0.025\\_\\% & B07 & 0.5255427 & FA-L & train\\_data & final & 0.6509444 & 0.6011040 & 1.950087 & 1.950087 & 0.279392 & Final (Train)\\\\\n", + "\t2 & 0.5255427 & -0.01121794 & -0.01121794 & LPS\\_0.010\\_ug\\_per\\_ml\\_DMSO\\_0.025\\_\\% & B08 & 0.5255427 & FA-L & train\\_data & final & 0.6692993 & 0.6434943 & 1.950087 & 1.950087 & 0.279392 & Final (Train)\\\\\n", + "\t3 & 0.5255427 & -0.01121794 & -0.01121794 & LPS\\_Nigericin\\_100.000\\_ug\\_per\\_ml\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & B10 & 0.5255427 & FA-L & train\\_data & final & 0.5639984 & 0.5341321 & 1.950087 & 1.950087 & 0.279392 & Final (Train)\\\\\n", + "\t4 & 0.5255427 & -0.01121794 & -0.01121794 & LPS\\_Nigericin\\_100.000\\_ug\\_per\\_ml\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & B11 & 0.5255427 & FA-L & train\\_data & final & 0.5898094 & 0.7169579 & 1.950087 & 1.950087 & 0.279392 & Final (Train)\\\\\n", + "\t5 & 0.5255427 & -0.01121794 & -0.01121794 & Media & B12 & 0.5255427 & FA-L & train\\_data & final & 0.6330056 & 0.5686943 & 1.950087 & 1.950087 & 0.279392 & Final (Train)\\\\\n", + "\t6 & 0.5255427 & -0.01121794 & -0.01121794 & LPS\\_Nigericin\\_100.000\\_ug\\_per\\_ml\\_3.000\\_uM\\_DMSO\\_0.025\\_\\% & C04 & 0.5255427 & FA-L & train\\_data & final & 0.4363507 & 0.6515227 & 1.950087 & 1.950087 & 0.279392 & Final (Train)\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", - "A data.frame: 6 × 15\n", + "A data.frame: 6 \u00d7 15\n", "\n", - "| | explained_variance <dbl> | neg_mean_absolute_error <dbl> | neg_mean_squared_error <dbl> | well <chr> | treatment <chr> | r2 <dbl> | cytokine <chr> | data_split <chr> | shuffle <chr> | predicted_value <dbl> | actual_value <dbl> | log10_neg_mean_absolute_error <dbl> | log10_neg_mean_squared_error <dbl> | log10_explained_variance <dbl> | shuffle_plus_data_split <fct> |\n", + "| | explained_variance <dbl> | neg_mean_absolute_error <dbl> | neg_mean_squared_error <dbl> | treatment <chr> | well <chr> | r2 <dbl> | cytokine <chr> | data_split <chr> | shuffle <chr> | predicted_value <dbl> | actual_value <dbl> | log10_neg_mean_absolute_error <dbl> | log10_neg_mean_squared_error <dbl> | log10_explained_variance <dbl> | shuffle_plus_data_split <fct> |\n", "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", - "| 1 | 1 | -0.12876296 | -0.016579900 | B05 | LPS_Nigericin_100.000_1.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.6226146 | 0.8902090 | 1.7804181 | 0 | Final (Train) |\n", - "| 2 | 1 | -0.09606601 | -0.009228678 | B08 | LPS_0.010_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.4031387 | 1.0174302 | 2.0348605 | 0 | Final (Train) |\n", - "| 3 | 1 | -0.21557860 | -0.046474132 | B10 | LPS_Nigericin_100.000_1.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.7073632 | 0.6663944 | 1.3327887 | 0 | Final (Train) |\n", - "| 4 | 1 | -0.57668367 | -0.332564053 | C02 | LPS_0.100_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.1619233 | 0.2390623 | 0.4781247 | 0 | Final (Train) |\n", - "| 5 | 1 | -0.11961401 | -0.014307512 | C05 | LPS_Nigericin_100.000_3.0_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.6136835 | 0.9222179 | 1.8444359 | 0 | Final (Train) |\n", - "| 6 | 1 | -0.31175502 | -0.097191194 | C06 | DMSO_0.100_DMSO_0.025 | 0 | GFbeta | train_data | final | 0.4969174 | 0.1925851 | 0.5061865 | 1.0123731 | 0 | Final (Train) |\n", + "| 1 | 0.5255427 | -0.01121794 | -0.01121794 | DMSO_0.100_%_DMSO_0.025_% | B07 | 0.5255427 | FA-L | train_data | final | 0.6509444 | 0.6011040 | 1.950087 | 1.950087 | 0.279392 | Final (Train) |\n", + "| 2 | 0.5255427 | -0.01121794 | -0.01121794 | LPS_0.010_ug_per_ml_DMSO_0.025_% | B08 | 0.5255427 | FA-L | train_data | final | 0.6692993 | 0.6434943 | 1.950087 | 1.950087 | 0.279392 | Final (Train) |\n", + "| 3 | 0.5255427 | -0.01121794 | -0.01121794 | LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_% | B10 | 0.5255427 | FA-L | train_data | final | 0.5639984 | 0.5341321 | 1.950087 | 1.950087 | 0.279392 | Final (Train) |\n", + "| 4 | 0.5255427 | -0.01121794 | -0.01121794 | LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_% | B11 | 0.5255427 | FA-L | train_data | final | 0.5898094 | 0.7169579 | 1.950087 | 1.950087 | 0.279392 | Final (Train) |\n", + "| 5 | 0.5255427 | -0.01121794 | -0.01121794 | Media | B12 | 0.5255427 | FA-L | train_data | final | 0.6330056 | 0.5686943 | 1.950087 | 1.950087 | 0.279392 | Final (Train) |\n", + "| 6 | 0.5255427 | -0.01121794 | -0.01121794 | LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_% | C04 | 0.5255427 | FA-L | train_data | final | 0.4363507 | 0.6515227 | 1.950087 | 1.950087 | 0.279392 | Final (Train) |\n", "\n" ], "text/plain": [ - " explained_variance neg_mean_absolute_error neg_mean_squared_error well\n", - "1 1 -0.12876296 -0.016579900 B05 \n", - "2 1 -0.09606601 -0.009228678 B08 \n", - "3 1 -0.21557860 -0.046474132 B10 \n", - "4 1 -0.57668367 -0.332564053 C02 \n", - "5 1 -0.11961401 -0.014307512 C05 \n", - "6 1 -0.31175502 -0.097191194 C06 \n", - " treatment r2 cytokine data_split shuffle\n", - "1 LPS_Nigericin_100.000_1.0_DMSO_0.025 0 GFbeta train_data final \n", - "2 LPS_0.010_DMSO_0.025 0 GFbeta train_data final \n", - "3 LPS_Nigericin_100.000_1.0_DMSO_0.025 0 GFbeta train_data final \n", - "4 LPS_0.100_DMSO_0.025 0 GFbeta train_data final \n", - "5 LPS_Nigericin_100.000_3.0_DMSO_0.025 0 GFbeta train_data final \n", - "6 DMSO_0.100_DMSO_0.025 0 GFbeta train_data final \n", - " predicted_value actual_value log10_neg_mean_absolute_error\n", - "1 0.4969174 0.6226146 0.8902090 \n", - "2 0.4969174 0.4031387 1.0174302 \n", - "3 0.4969174 0.7073632 0.6663944 \n", - "4 0.4969174 0.1619233 0.2390623 \n", - "5 0.4969174 0.6136835 0.9222179 \n", - "6 0.4969174 0.1925851 0.5061865 \n", + " explained_variance neg_mean_absolute_error neg_mean_squared_error\n", + "1 0.5255427 -0.01121794 -0.01121794 \n", + "2 0.5255427 -0.01121794 -0.01121794 \n", + "3 0.5255427 -0.01121794 -0.01121794 \n", + "4 0.5255427 -0.01121794 -0.01121794 \n", + "5 0.5255427 -0.01121794 -0.01121794 \n", + "6 0.5255427 -0.01121794 -0.01121794 \n", + " treatment well r2 cytokine\n", + "1 DMSO_0.100_%_DMSO_0.025_% B07 0.5255427 FA-L \n", + "2 LPS_0.010_ug_per_ml_DMSO_0.025_% B08 0.5255427 FA-L \n", + "3 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_% B10 0.5255427 FA-L \n", + "4 LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_% B11 0.5255427 FA-L \n", + "5 Media B12 0.5255427 FA-L \n", + "6 LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_% C04 0.5255427 FA-L \n", + " data_split shuffle predicted_value actual_value log10_neg_mean_absolute_error\n", + "1 train_data final 0.6509444 0.6011040 1.950087 \n", + "2 train_data final 0.6692993 0.6434943 1.950087 \n", + "3 train_data final 0.5639984 0.5341321 1.950087 \n", + "4 train_data final 0.5898094 0.7169579 1.950087 \n", + "5 train_data final 0.6330056 0.5686943 1.950087 \n", + "6 train_data final 0.4363507 0.6515227 1.950087 \n", " log10_neg_mean_squared_error log10_explained_variance shuffle_plus_data_split\n", - "1 1.7804181 0 Final (Train) \n", - "2 2.0348605 0 Final (Train) \n", - "3 1.3327887 0 Final (Train) \n", - "4 0.4781247 0 Final (Train) \n", - "5 1.8444359 0 Final (Train) \n", - "6 1.0123731 0 Final (Train) " + "1 1.950087 0.279392 Final (Train) \n", + "2 1.950087 0.279392 Final (Train) \n", + "3 1.950087 0.279392 Final (Train) \n", + "4 1.950087 0.279392 Final (Train) \n", + "5 1.950087 0.279392 Final (Train) \n", + "6 1.950087 0.279392 Final (Train) " ] }, "metadata": {}, @@ -1012,7 +790,7 @@ "# calculate the se of each metric for each shuffle, data_split, and cytokine in R\n", "agg_df <- aggregate(r2 ~ shuffle_plus_data_split, df_stats, function(x) c(mean = mean(x), sd = sd(x)))\n", "# split the log10_neg_mean_absolute_error column into two columns\n", - "agg_df <- cbind(agg_df, agg_df$r2)\n", + "agg_df <- cbind(df_stats, df_stats$r2)\n", "# remove the log10_neg_mean_absolute_error column by name\n", "agg_df <- agg_df[, !names(agg_df) %in% c('r2')]\n", "# rename the columns \n", @@ -1023,7 +801,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": { "vscode": { "languageId": "r" @@ -1037,7 +815,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": { "vscode": { "languageId": "r" @@ -1046,7 +824,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -1107,7 +885,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": { "vscode": { "languageId": "r" @@ -1125,7 +903,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": { "vscode": { "languageId": "r" @@ -1176,7 +954,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": { "vscode": { "languageId": "r" @@ -1218,7 +996,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": { "vscode": { "languageId": "r" @@ -1250,7 +1028,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "metadata": { "vscode": { "languageId": "r" @@ -1269,7 +1047,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": { "vscode": { "languageId": "r" @@ -1281,18 +1059,18 @@ "output_type": "stream", "text": [ "Warning message:\n", - "“\u001b[1m\u001b[22mExpected 6 pieces. Additional pieces discarded in 228 rows [4, 11, 16, 18, 21,\n", - "22, 24, 29, 31, 36, 37, 38, 40, 43, 44, 45, 48, 63, 69, 74, ...].”\n", + "\u201c\u001b[1m\u001b[22mExpected 6 pieces. Additional pieces discarded in 228 rows [4, 11, 16, 18, 21,\n", + "22, 24, 29, 31, 36, 37, 38, 40, 43, 44, 45, 48, 63, 69, 74, ...].\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mExpected 6 pieces. Missing pieces filled with `NA` in 323 rows [1, 2, 3, 5, 7,\n", - "8, 10, 12, 13, 14, 15, 17, 20, 23, 25, 26, 27, 28, 30, 33, ...].”\n" + "\u201c\u001b[1m\u001b[22mExpected 6 pieces. Missing pieces filled with `NA` in 323 rows [1, 2, 3, 5, 7,\n", + "8, 10, 12, 13, 14, 15, 17, 20, 23, 25, 26, 27, 28, 30, 33, ...].\u201d\n" ] }, { "data": { "text/html": [ "\n", - "\n", + "\n", "\n", "\t\n", "\t\n", @@ -1308,7 +1086,7 @@ "
A grouped_df: 6 × 16A grouped_df: 6 \u00d7 16
feature_namescompartmentfeature_groupmeasurementchannelparameter1parameter2coefficientssecreted_proteinsshufflecell_typealphal1_ratior2channel_cleanedchannel_learned
<chr><chr><chr><chr><chr><chr><chr><dbl><chr><chr><chr><dbl><dbl><dbl><chr><chr>
\n" ], "text/latex": [ - "A grouped\\_df: 6 × 16\n", + "A grouped\\_df: 6 \u00d7 16\n", "\\begin{tabular}{llllllllllllllll}\n", " feature\\_names & compartment & feature\\_group & measurement & channel & parameter1 & parameter2 & coefficients & secreted\\_proteins & shuffle & cell\\_type & alpha & l1\\_ratio & r2 & channel\\_cleaned & channel\\_learned\\\\\n", " & & & & & & & & & & & & & & & \\\\\n", @@ -1323,7 +1101,7 @@ ], "text/markdown": [ "\n", - "A grouped_df: 6 × 16\n", + "A grouped_df: 6 \u00d7 16\n", "\n", "| feature_names <chr> | compartment <chr> | feature_group <chr> | measurement <chr> | channel <chr> | parameter1 <chr> | parameter2 <chr> | coefficients <dbl> | secreted_proteins <chr> | shuffle <chr> | cell_type <chr> | alpha <dbl> | l1_ratio <dbl> | r2 <dbl> | channel_cleaned <chr> | channel_learned <chr> |\n", "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", @@ -1441,7 +1219,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "metadata": { "vscode": { "languageId": "r" @@ -1455,7 +1233,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": { "vscode": { "languageId": "r" @@ -1474,7 +1252,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "metadata": { "vscode": { "languageId": "r" @@ -1677,7 +1455,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "metadata": { "vscode": { "languageId": "r" @@ -1691,7 +1469,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "metadata": { "vscode": { "languageId": "r" @@ -1707,7 +1485,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 30, "metadata": { "vscode": { "languageId": "r" @@ -1719,11 +1497,11 @@ "output_type": "stream", "text": [ "Warning message:\n", - "“\u001b[1m\u001b[22mExpected 6 pieces. Additional pieces discarded in 228 rows [27, 29, 30, 32, 33,\n", - "35, 51, 55, 56, 58, 61, 62, 66, 71, 72, 73, 76, 86, 89, 101, ...].”\n", + "\u201c\u001b[1m\u001b[22mExpected 6 pieces. Additional pieces discarded in 228 rows [16, 22, 38, 44, 46,\n", + "51, 55, 65, 66, 73, 75, 90, 95, 96, 97, 101, 104, 115, 119, 120, ...].\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mExpected 6 pieces. Missing pieces filled with `NA` in 323 rows [1, 2, 4, 5, 6,\n", - "7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, ...].”\n" + "\u201c\u001b[1m\u001b[22mExpected 6 pieces. Missing pieces filled with `NA` in 323 rows [1, 2, 3, 5, 6,\n", + "7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 24, 25, ...].\u201d\n" ] } ], @@ -1764,7 +1542,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 31, "metadata": { "vscode": { "languageId": "r" @@ -1800,7 +1578,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 32, "metadata": { "vscode": { "languageId": "r" @@ -1812,11 +1590,11 @@ "output_type": "stream", "text": [ "Warning message:\n", - "“\u001b[1m\u001b[22mExpected 6 pieces. Additional pieces discarded in 83 rows [66, 67, 68, 69, 70,\n", - "71, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, ...].”\n", + "\u201c\u001b[1m\u001b[22mExpected 6 pieces. Additional pieces discarded in 83 rows [66, 67, 68, 69, 70,\n", + "71, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, ...].\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mExpected 6 pieces. Missing pieces filled with `NA` in 175 rows [1, 2, 3, 4, 5,\n", - "6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].”\n" + "\u201c\u001b[1m\u001b[22mExpected 6 pieces. Missing pieces filled with `NA` in 175 rows [1, 2, 3, 4, 5,\n", + "6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].\u201d\n" ] } ], @@ -1952,7 +1730,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 33, "metadata": { "vscode": { "languageId": "r" @@ -1974,7 +1752,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -2028,7 +1806,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 34, "metadata": { "vscode": { "languageId": "r" @@ -2057,7 +1835,7 @@ { "data": { "text/plain": [ - "rastergrob[GRID.rastergrob.2832] " + "rastergrob[GRID.rastergrob.2830] " ] }, "metadata": {}, @@ -2080,7 +1858,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 35, "metadata": { "vscode": { "languageId": "r" @@ -2094,8 +1872,7 @@ "variance_r2_plot_local <- variance_r2_plot_local + theme(plot.title = element_blank())\n", "IL1beta_a_v_p <- IL1beta_a_v_p + theme(plot.title = element_blank())\n", "model_performance_il1b <- model_performance_il1b + theme(plot.title = element_blank())\n", - "il1beta_final_plot <- il1beta_final_plot + theme(plot.title = element_blank())\n", - "# model_heatmap <- model_heatmap + theme(plot.title = element_blank())" + "il1beta_final_plot <- il1beta_final_plot + theme(plot.title = element_blank())\n" ] }, { @@ -2105,53 +1882,6 @@ "## Mean Average Precision plots" ] }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [], - "source": [ - "# set path to the data morphology\n", - "# class\n", - "reg_df_morphology_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_regular_class.csv\")\n", - "shuffled_morphology_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_shuffled_feature_space_class.csv\")\n", - "# treatment \n", - "reg_df_morphology_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_regular_treatment.csv\")\n", - "shuffled_morphology_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_shuffled_feature_space_treatment.csv\")\n", - "\n", - "# set path to the secretome data\n", - "# class\n", - "reg_df_secretome_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_regular_class.csv\")\n", - "shuffled_secretome_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_shuffled_feature_space_class.csv\")\n", - "# treatment\n", - "reg_df_secretome_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_regular_treatment.csv\")\n", - "shuffled_secretome_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_shuffled_feature_space_treatment.csv\")\n", - "\n", - "# read in the data\n", - "reg_df_morphology_class <- read.csv(reg_df_morphology_class_path)\n", - "shuffled_morphology_class <- read.csv(shuffled_morphology_class_path)\n", - "\n", - "reg_df_morphology_treatment <- read.csv(reg_df_morphology_treatment_path)\n", - "shuffled_morphology_treatment <- read.csv(shuffled_morphology_treatment_path)\n", - "\n", - "reg_df_secretome_class <- read.csv(reg_df_secretome_class_path)\n", - "shuffled_secretome_class <- read.csv(shuffled_secretome_class_path)\n", - "\n", - "reg_df_secretome_treatment <- read.csv(reg_df_secretome_treatment_path)\n", - "shuffled_secretome_treatment <- read.csv(shuffled_secretome_treatment_path)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Clean the class data" - ] - }, { "cell_type": "code", "execution_count": 36, @@ -2162,53 +1892,9 @@ }, "outputs": [], "source": [ - "levels_list <- c(\n", - " 'Media',\n", - " 'DMSO_0.100_%_DMSO_0.025_%',\n", - " 'DMSO_0.100_%_DMSO_1.000_%',\n", - " 'DMSO_0.100_%_Z-VAD-FMK_30.000_uM',\n", - " 'DMSO_0.100_%_Z-VAD-FMK_100.000_uM',\n", - "\n", - " 'Disulfiram_0.100_uM_DMSO_0.025_%',\n", - " 'Disulfiram_1.000_uM_DMSO_0.025_%',\n", - " 'Disulfiram_2.500_uM_DMSO_0.025_%',\n", - " \n", - " 'Flagellin_0.100_ug_per_ml_DMSO_0.025_%',\n", - " 'Flagellin_1.000_ug_per_ml_DMSO_0.025_%',\n", - " 'Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM',\n", - " \n", - " 'LPS_0.010_ug_per_ml_DMSO_0.025_%',\n", - " 'LPS_0.100_ug_per_ml_DMSO_0.025_%',\n", - " 'LPS_1.000_ug_per_ml_DMSO_0.025_%',\n", - "\n", - " 'LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM',\n", - " 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM',\n", - "\n", - " 'LPS_10.000_ug_per_ml_DMSO_0.025_%',\n", - " 'LPS_10.000_ug_per_ml_Disulfiram_0.100_uM',\n", - " 'LPS_10.000_ug_per_ml_Disulfiram_1.000_uM',\n", - " 'LPS_10.000_ug_per_ml_Disulfiram_2.500_uM',\n", - " 'LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM',\n", - " \n", - " 'LPS_100.000_ug_per_ml_DMSO_0.025_%',\n", - " 'LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%',\n", - " 'LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%',\n", - "\n", - " 'H2O2_100.000_nM_DMSO_0.025_%',\n", - " 'H2O2_100.000_uM_DMSO_0.025_%',\n", - " 'H2O2_100.000_uM_Disulfiram_1.000_uM',\n", - " 'H2O2_100.000_uM_Z-VAD-FMK_100.000_uM',\n", - " 'Thapsigargin_1.000_uM_DMSO_0.025_%',\n", - " 'Thapsigargin_10.000_uM_DMSO_0.025_%',\n", + "map_df_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology_secretome_comparison.parquet\")\n", "\n", - " 'Topotecan_5.000_nM_DMSO_0.025_%', \n", - " 'Topotecan_10.000_nM_DMSO_0.025_%',\n", - " 'Topotecan_20.000_nM_DMSO_0.025_%'\n", - ")" + "map_df <- arrow::read_parquet(map_df_path)" ] }, { @@ -2219,258 +1905,10 @@ "languageId": "r" } }, - "outputs": [], - "source": [ - "# combine the dataframes\n", - "all_df_morphology_class <- rbind(reg_df_morphology_class, shuffled_morphology_class)\n", - "all_df_morphology_treatment <- rbind(reg_df_morphology_treatment, shuffled_morphology_treatment)\n", - "all_df_secretome_class <- rbind(reg_df_secretome_class, shuffled_secretome_class)\n", - "all_df_secretome_treatment <- rbind(reg_df_secretome_treatment, shuffled_secretome_treatment)\n", - "\n", - "all_df_morphology_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_morphology_class$shuffled)\n", - "all_df_morphology_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_morphology_class$shuffled)\n", - "all_df_morphology_class$shuffled <- factor(all_df_morphology_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_morphology_class$Metadata_labels <- factor(all_df_morphology_class$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", - "\n", - "all_df_secretome_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_secretome_class$shuffled)\n", - "all_df_secretome_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_secretome_class$shuffled)\n", - "all_df_secretome_class$shuffled <- factor(all_df_secretome_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "\n", - "all_df_morphology_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_morphology_treatment$shuffled)\n", - "all_df_morphology_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_morphology_treatment$shuffled)\n", - "all_df_morphology_treatment$shuffled <- factor(all_df_morphology_treatment$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)\n", - "\n", - "all_df_secretome_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_secretome_treatment$shuffled)\n", - "all_df_secretome_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_secretome_treatment$shuffled)\n", - "all_df_secretome_treatment$shuffled <- factor(all_df_secretome_treatment$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 5
shuffledMetadata_labelsoneb_Metadata_Treatment_Dose_Inhibitor_Dosemorphology_apsecretome_ap
<fct><chr><fct><dbl><dbl>
1Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
2Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
3Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
4Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
5Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
6Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
\n" - ], - "text/latex": [ - "A data.frame: 6 × 5\n", - "\\begin{tabular}{r|lllll}\n", - " & shuffled & Metadata\\_labels & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t2 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t3 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t4 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t5 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t6 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 5\n", - "\n", - "| | shuffled <fct> | Metadata_labels <chr> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 2 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 3 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 4 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 5 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 6 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "1 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "2 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "3 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "4 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "5 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "6 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - " morphology_ap secretome_ap\n", - "1 0.7666667 1 \n", - "2 0.7666667 1 \n", - "3 0.7666667 1 \n", - "4 0.7666667 1 \n", - "5 0.7666667 1 \n", - "6 0.7666667 1 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# cobine the dfs\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_morphology_treatment <- all_df_morphology_treatment[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\",\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\")]\n", - "# rename the average_precision column to moprhology_ap\n", - "colnames(subset_morphology_treatment)[colnames(subset_morphology_treatment)==\"average_precision\"] <- \"morphology_ap\"\n", - "\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_secretome_treatment <- all_df_secretome_treatment[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\",\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\")]\n", - "# rename the average_precision column to secretome_ap\n", - "colnames(subset_secretome_treatment)[colnames(subset_secretome_treatment)==\"average_precision\"] <- \"secretome_ap\"\n", - "\n", - "# merge the dataframes\n", - "merged_df <- merge(subset_morphology_treatment, subset_secretome_treatment, by=c(\"shuffled\", \"Metadata_labels\", \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"))\n", - "head(merged_df)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## mAP Scatter compare plot" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 × 6
shuffledMetadata_labelsoneb_Metadata_Treatment_Dose_Inhibitor_Dosemorphology_apsecretome_apgroup
<fct><chr><dbl><dbl><dbl><fct>
Non-shuffledApoptosis 33.5000000.81607141.0000000Non-shuffled\n", - "Apoptosis
Shuffled Apoptosis 33.5000000.41502981.0000000NA
Non-shuffledControl 3.6976740.69671150.2272906NA
Shuffled Control 3.6976740.67605640.1932395NA
Non-shuffledPyroptosis18.1666670.88502540.5088862NA
Shuffled Pyroptosis18.1666670.46204510.1463034NA
\n" - ], - "text/latex": [ - "A data.frame: 6 × 6\n", - "\\begin{tabular}{llllll}\n", - " shuffled & Metadata\\_labels & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & morphology\\_ap & secretome\\_ap & group\\\\\n", - " & & & & & \\\\\n", - "\\hline\n", - "\t Non-shuffled & Apoptosis & 33.500000 & 0.8160714 & 1.0000000 & Non-shuffled\n", - "Apoptosis\\\\\n", - "\t Shuffled & Apoptosis & 33.500000 & 0.4150298 & 1.0000000 & NA \\\\\n", - "\t Non-shuffled & Control & 3.697674 & 0.6967115 & 0.2272906 & NA \\\\\n", - "\t Shuffled & Control & 3.697674 & 0.6760564 & 0.1932395 & NA \\\\\n", - "\t Non-shuffled & Pyroptosis & 18.166667 & 0.8850254 & 0.5088862 & NA \\\\\n", - "\t Shuffled & Pyroptosis & 18.166667 & 0.4620451 & 0.1463034 & NA \\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 × 6\n", - "\n", - "| shuffled <fct> | Metadata_labels <chr> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <dbl> | morphology_ap <dbl> | secretome_ap <dbl> | group <fct> |\n", - "|---|---|---|---|---|---|\n", - "| Non-shuffled | Apoptosis | 33.500000 | 0.8160714 | 1.0000000 | Non-shuffled\n", - "Apoptosis |\n", - "| Shuffled | Apoptosis | 33.500000 | 0.4150298 | 1.0000000 | NA |\n", - "| Non-shuffled | Control | 3.697674 | 0.6967115 | 0.2272906 | NA |\n", - "| Shuffled | Control | 3.697674 | 0.6760564 | 0.1932395 | NA |\n", - "| Non-shuffled | Pyroptosis | 18.166667 | 0.8850254 | 0.5088862 | NA |\n", - "| Shuffled | Pyroptosis | 18.166667 | 0.4620451 | 0.1463034 | NA |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "1 Non-shuffled Apoptosis 33.500000 \n", - "2 Shuffled Apoptosis 33.500000 \n", - "3 Non-shuffled Control 3.697674 \n", - "4 Shuffled Control 3.697674 \n", - "5 Non-shuffled Pyroptosis 18.166667 \n", - "6 Shuffled Pyroptosis 18.166667 \n", - " morphology_ap secretome_ap group \n", - "1 0.8160714 1.0000000 Non-shuffled\\nApoptosis\n", - "2 0.4150298 1.0000000 NA \n", - "3 0.6967115 0.2272906 NA \n", - "4 0.6760564 0.1932395 NA \n", - "5 0.8850254 0.5088862 NA \n", - "6 0.4620451 0.1463034 NA " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# aggregate the data by shuffled and Metadata_labels\n", - "merged_agg <- aggregate(. ~ shuffled + Metadata_labels, data=merged_df, FUN=mean)\n", - "# combine the shuffled and Metadata_labels columns\n", - "merged_agg$group <- paste(merged_agg$shuffled, merged_agg$Metadata_labels, sep=\"_\")\n", - "# change the text in the group column\n", - "merged_agg$group <- gsub(\"Non-shuffled Control\", \"Non-shuffled\\nControl\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Control\", \"Shuffled\\nControl\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Non-shuffled_Apoptosis\", \"Non-shuffled\\nApoptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Apoptosis\", \"Shuffled\\nApoptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Non-shuffled Pyroptosis\", \"Non-shuffled\\nPyroptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Pyroptosis\", \"Shuffled\\nPyroptosis\", merged_agg$group)\n", - "# make the group column a factor\n", - "merged_agg$group <- factor(\n", - " merged_agg$group, \n", - " levels = c(\n", - " \"Non-shuffled\\nControl\", \n", - " \"Shuffled features\\nControl\", \n", - " \"Shuffled phenotypes\\nControl\", \n", - "\n", - " \"Non-shuffled\\nApoptosis\", \n", - " \"Shuffled features\\nApoptosis\", \n", - " \"Shuffled phenotypes\\nApoptosis\",\n", - " \n", - " \"Non-shuffled\\nPyroptosis\",\n", - " \"Shuffled features\\nPyroptosis\", \n", - " \"Shuffled phenotypes\\nPyroptosis\"))\n", - "\n", - "merged_agg" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": { - "vscode": { - "languageId": "r" - } - }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -2485,14 +1923,13 @@ } ], "source": [ - "# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled\n", - "merged_agg <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels, data=merged_df, FUN=mean)\n", "# scatter plot\n", "scatter_compare_treatment <- (\n", - " ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled))\n", - " + geom_point(size=3, alpha=0.7)\n", + " ggplot(map_df, aes(x=mAP_moprhology, y=mAP_secretome, col = Metadata_labels, shape=shuffled))\n", + " + geom_point(size=3, alpha=0.5)\n", " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", " + theme_bw()\n", + " + ggtitle(\"Comparison of mAP scores\")\n", " + ylim(0,1)\n", " + xlim(0,1)\n", " # Change the legend title\n", @@ -2520,17 +1957,23 @@ " )\n", ")\n", " + figure_theme\n", + " + ggplot2::coord_fixed(ratio = 1)\n", " # add y = x line\n", " + geom_abline(intercept = 0, slope = 1, linetype=\"dashed\", color = \"black\")\n", - " # fix the coord\n", - " + ggplot2::coord_fixed(ratio = 1)\n", ")\n", "scatter_compare_treatment" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Final plot" + ] + }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 38, "metadata": { "vscode": { "languageId": "r" @@ -2542,11 +1985,11 @@ "output_type": "stream", "text": [ "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 26 rows containing non-finite outside the scale range\n", - "(`stat_smooth()`).”\n", + "\u201c\u001b[1m\u001b[22mRemoved 30 rows containing non-finite outside the scale range\n", + "(`stat_smooth()`).\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 26 rows containing missing values or values outside the scale range\n", - "(`geom_point()`).”\n" + "\u201c\u001b[1m\u001b[22mRemoved 30 rows containing missing values or values outside the scale range\n", + "(`geom_point()`).\u201d\n" ] }, { @@ -2573,16 +2016,16 @@ "output_type": "stream", "text": [ "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 26 rows containing non-finite outside the scale range\n", - "(`stat_smooth()`).”\n", + "\u201c\u001b[1m\u001b[22mRemoved 30 rows containing non-finite outside the scale range\n", + "(`stat_smooth()`).\u201d\n", "Warning message:\n", - "“\u001b[1m\u001b[22mRemoved 26 rows containing missing values or values outside the scale range\n", - "(`geom_point()`).”\n" + "\u201c\u001b[1m\u001b[22mRemoved 30 rows containing missing values or values outside the scale range\n", + "(`geom_point()`).\u201d\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] diff --git a/figures/4.figure4/scripts/figure4.r b/figures/4.figure4/scripts/figure4.r index cfa8c0b64..e1365ea03 100644 --- a/figures/4.figure4/scripts/figure4.r +++ b/figures/4.figure4/scripts/figure4.r @@ -24,11 +24,11 @@ cell_type <- "PBMC" # set the path to the data files df_stats_path <- file.path( - paste0("../../../6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/",cell_type,"/aggregated_with_nomic/model_stats.csv" + paste0("../../../6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/",cell_type,"_aggregated_with_nomic/model_stats.csv" ) ) df_variance_path <- file.path( - paste0("../../../6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/",cell_type,"/aggregated_with_nomic/variance_r2_stats.csv" + paste0("../../../6.bulk_Morphology_Elastic_Network/2.test_model/results/regression/",cell_type,"_aggregated_with_nomic/variance_r2_stats.csv" ) ) @@ -45,8 +45,6 @@ df_stats <- read.csv(df_stats_path) df_variance <- read.csv(df_variance_path) -head(df_stats) -head(df_variance) # remove '[]' from the string in the column df_variance$r2 <- gsub("\\[|\\]", "", df_variance$r2) # set the column as numeric @@ -129,7 +127,6 @@ df_stats$shuffle_plus_data_split <- gsub("final_train_data", "Final (Train)", df df_stats$shuffle_plus_data_split <- gsub("shuffled_baseline_test_data", "Shuffled (Test)", df_stats$shuffle_plus_data_split) df_stats$shuffle_plus_data_split <- gsub("shuffled_baseline_train_data", "Shuffled (Train)", df_stats$shuffle_plus_data_split) - options(repr.plot.width=6, repr.plot.height=5) # set output path global_prediction_trend_path <- file.path(paste0(enet_cp_fig_path,"global_prediction_trend.png")) @@ -211,6 +208,8 @@ df_stats$shuffle_plus_data_split <- factor( ) ) + + enet_cp_fig <- file.path(paste0(enet_cp_fig_path,"Predicted_vs_Actual_all_cytokines.png")) # set plot size width <- 7 @@ -258,7 +257,8 @@ tmp_df <- aggregate(mean_log10_neg_mean_absolute_error ~ shuffle + data_split, t tmp_df <- cbind(tmp_df, tmp_df$mean_log10_neg_mean_absolute_error) # drop the log10_neg_mean_absolute_error column by name tmp_df <- tmp_df[, !names(tmp_df) %in% c('mean_log10_neg_mean_absolute_error')] -# split the mean_log10_neg_mean_absolute_error column into two columns + + model_performance_il1b <- ( ggplot(tmp_df, aes(x=data_split, y=mean, fill=shuffle)) @@ -273,12 +273,10 @@ model_performance_il1b <- ( model_performance_il1b -head(df_stats) - # calculate the se of each metric for each shuffle, data_split, and cytokine in R agg_df <- aggregate(r2 ~ shuffle_plus_data_split, df_stats, function(x) c(mean = mean(x), sd = sd(x))) # split the log10_neg_mean_absolute_error column into two columns -agg_df <- cbind(agg_df, agg_df$r2) +agg_df <- cbind(df_stats, df_stats$r2) # remove the log10_neg_mean_absolute_error column by name agg_df <- agg_df[, !names(agg_df) %in% c('r2')] # rename the columns @@ -843,13 +841,14 @@ row_ha_2 <- rowAnnotation( annotation_name_side = "bottom", annotation_name_gp = gpar(fontsize = 16), col = list( - Feature_Type = c( - "AreaShape" = brewer.pal(6, "Dark2")[1], - "Correlation" = brewer.pal(6, "Dark2")[2], - "Granularity" = brewer.pal(6, "Dark2")[3], - "Neighbors" = brewer.pal(6, "Dark2")[4], - "RadialDistribution" = brewer.pal(6, "Dark2")[5], - "Texture" = brewer.pal(6, "Dark2")[6] + FeatureType = c( + "AreaShape" = brewer.pal(7, "Dark2")[1], + "Correlation" = brewer.pal(7, "Dark2")[2], + "Granularity" = brewer.pal(7, "Dark2")[3], + "Intensity" = brewer.pal(7, "Dark2")[4], + "Neighbors" = brewer.pal(7, "Dark2")[5], + "RadialDistribution" = brewer.pal(7, "Dark2")[6], + "Texture" = brewer.pal(7, "Dark2")[7] ) ) ) @@ -950,162 +949,19 @@ variance_r2_plot_local <- variance_r2_plot_local + theme(plot.title = element_bl IL1beta_a_v_p <- IL1beta_a_v_p + theme(plot.title = element_blank()) model_performance_il1b <- model_performance_il1b + theme(plot.title = element_blank()) il1beta_final_plot <- il1beta_final_plot + theme(plot.title = element_blank()) -# model_heatmap <- model_heatmap + theme(plot.title = element_blank()) - -# set path to the data morphology -# class -reg_df_morphology_class_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","mAP_scores_regular_class.csv") -shuffled_morphology_class_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","mAP_scores_shuffled_feature_space_class.csv") -# treatment -reg_df_morphology_treatment_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","mAP_scores_regular_treatment.csv") -shuffled_morphology_treatment_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","mAP_scores_shuffled_feature_space_treatment.csv") - -# set path to the secretome data -# class -reg_df_secretome_class_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","mAP_scores_regular_class.csv") -shuffled_secretome_class_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","mAP_scores_shuffled_feature_space_class.csv") -# treatment -reg_df_secretome_treatment_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","mAP_scores_regular_treatment.csv") -shuffled_secretome_treatment_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","mAP_scores_shuffled_feature_space_treatment.csv") - -# read in the data -reg_df_morphology_class <- read.csv(reg_df_morphology_class_path) -shuffled_morphology_class <- read.csv(shuffled_morphology_class_path) - -reg_df_morphology_treatment <- read.csv(reg_df_morphology_treatment_path) -shuffled_morphology_treatment <- read.csv(shuffled_morphology_treatment_path) - -reg_df_secretome_class <- read.csv(reg_df_secretome_class_path) -shuffled_secretome_class <- read.csv(shuffled_secretome_class_path) - -reg_df_secretome_treatment <- read.csv(reg_df_secretome_treatment_path) -shuffled_secretome_treatment <- read.csv(shuffled_secretome_treatment_path) - -levels_list <- c( - 'Media', - 'DMSO_0.100_%_DMSO_0.025_%', - 'DMSO_0.100_%_DMSO_1.000_%', - 'DMSO_0.100_%_Z-VAD-FMK_30.000_uM', - 'DMSO_0.100_%_Z-VAD-FMK_100.000_uM', - - 'Disulfiram_0.100_uM_DMSO_0.025_%', - 'Disulfiram_1.000_uM_DMSO_0.025_%', - 'Disulfiram_2.500_uM_DMSO_0.025_%', - - 'Flagellin_0.100_ug_per_ml_DMSO_0.025_%', - 'Flagellin_1.000_ug_per_ml_DMSO_0.025_%', - 'Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM', - - 'LPS_0.010_ug_per_ml_DMSO_0.025_%', - 'LPS_0.100_ug_per_ml_DMSO_0.025_%', - 'LPS_1.000_ug_per_ml_DMSO_0.025_%', - - 'LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM', - 'LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM', - - 'LPS_10.000_ug_per_ml_DMSO_0.025_%', - 'LPS_10.000_ug_per_ml_Disulfiram_0.100_uM', - 'LPS_10.000_ug_per_ml_Disulfiram_1.000_uM', - 'LPS_10.000_ug_per_ml_Disulfiram_2.500_uM', - 'LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM', - - 'LPS_100.000_ug_per_ml_DMSO_0.025_%', - 'LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%', - 'LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%', - - 'H2O2_100.000_nM_DMSO_0.025_%', - 'H2O2_100.000_uM_DMSO_0.025_%', - 'H2O2_100.000_uM_Disulfiram_1.000_uM', - 'H2O2_100.000_uM_Z-VAD-FMK_100.000_uM', - 'Thapsigargin_1.000_uM_DMSO_0.025_%', - 'Thapsigargin_10.000_uM_DMSO_0.025_%', - - 'Topotecan_5.000_nM_DMSO_0.025_%', - 'Topotecan_10.000_nM_DMSO_0.025_%', - 'Topotecan_20.000_nM_DMSO_0.025_%' -) -# combine the dataframes -all_df_morphology_class <- rbind(reg_df_morphology_class, shuffled_morphology_class) -all_df_morphology_treatment <- rbind(reg_df_morphology_treatment, shuffled_morphology_treatment) -all_df_secretome_class <- rbind(reg_df_secretome_class, shuffled_secretome_class) -all_df_secretome_treatment <- rbind(reg_df_secretome_treatment, shuffled_secretome_treatment) - -all_df_morphology_class$shuffled <- gsub("shuffled", "Shuffled", all_df_morphology_class$shuffled) -all_df_morphology_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_morphology_class$shuffled) -all_df_morphology_class$shuffled <- factor(all_df_morphology_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_morphology_class$Metadata_labels <- factor(all_df_morphology_class$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) - -all_df_secretome_class$shuffled <- gsub("shuffled", "Shuffled", all_df_secretome_class$shuffled) -all_df_secretome_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_secretome_class$shuffled) -all_df_secretome_class$shuffled <- factor(all_df_secretome_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) - -all_df_morphology_treatment$shuffled <- gsub("shuffled", "Shuffled", all_df_morphology_treatment$shuffled) -all_df_morphology_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_morphology_treatment$shuffled) -all_df_morphology_treatment$shuffled <- factor(all_df_morphology_treatment$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - -all_df_secretome_treatment$shuffled <- gsub("shuffled", "Shuffled", all_df_secretome_treatment$shuffled) -all_df_secretome_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_secretome_treatment$shuffled) -all_df_secretome_treatment$shuffled <- factor(all_df_secretome_treatment$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - -# cobine the dfs -# get the average precision, shuffled, and Metadata_labels columns by name -subset_morphology_treatment <- all_df_morphology_treatment[,c("average_precision", "shuffled", "Metadata_labels","oneb_Metadata_Treatment_Dose_Inhibitor_Dose")] -# rename the average_precision column to moprhology_ap -colnames(subset_morphology_treatment)[colnames(subset_morphology_treatment)=="average_precision"] <- "morphology_ap" - -# get the average precision, shuffled, and Metadata_labels columns by name -subset_secretome_treatment <- all_df_secretome_treatment[,c("average_precision", "shuffled", "Metadata_labels","oneb_Metadata_Treatment_Dose_Inhibitor_Dose")] -# rename the average_precision column to secretome_ap -colnames(subset_secretome_treatment)[colnames(subset_secretome_treatment)=="average_precision"] <- "secretome_ap" - -# merge the dataframes -merged_df <- merge(subset_morphology_treatment, subset_secretome_treatment, by=c("shuffled", "Metadata_labels", "oneb_Metadata_Treatment_Dose_Inhibitor_Dose")) -head(merged_df) - -# aggregate the data by shuffled and Metadata_labels -merged_agg <- aggregate(. ~ shuffled + Metadata_labels, data=merged_df, FUN=mean) -# combine the shuffled and Metadata_labels columns -merged_agg$group <- paste(merged_agg$shuffled, merged_agg$Metadata_labels, sep="_") -# change the text in the group column -merged_agg$group <- gsub("Non-shuffled Control", "Non-shuffled\nControl", merged_agg$group) -merged_agg$group <- gsub("Shuffled Control", "Shuffled\nControl", merged_agg$group) -merged_agg$group <- gsub("Non-shuffled_Apoptosis", "Non-shuffled\nApoptosis", merged_agg$group) -merged_agg$group <- gsub("Shuffled Apoptosis", "Shuffled\nApoptosis", merged_agg$group) -merged_agg$group <- gsub("Non-shuffled Pyroptosis", "Non-shuffled\nPyroptosis", merged_agg$group) -merged_agg$group <- gsub("Shuffled Pyroptosis", "Shuffled\nPyroptosis", merged_agg$group) -# make the group column a factor -merged_agg$group <- factor( - merged_agg$group, - levels = c( - "Non-shuffled\nControl", - "Shuffled features\nControl", - "Shuffled phenotypes\nControl", - - "Non-shuffled\nApoptosis", - "Shuffled features\nApoptosis", - "Shuffled phenotypes\nApoptosis", - "Non-shuffled\nPyroptosis", - "Shuffled features\nPyroptosis", - "Shuffled phenotypes\nPyroptosis")) +map_df_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology_secretome_comparison.parquet") -merged_agg +map_df <- arrow::read_parquet(map_df_path) -# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled -merged_agg <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels, data=merged_df, FUN=mean) # scatter plot scatter_compare_treatment <- ( - ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled)) - + geom_point(size=3, alpha=0.7) + ggplot(map_df, aes(x=mAP_moprhology, y=mAP_secretome, col = Metadata_labels, shape=shuffled)) + + geom_point(size=3, alpha=0.5) + labs(x="Morphology mAP score", y="Secretome mAP score") + theme_bw() + + ggtitle("Comparison of mAP scores") + ylim(0,1) + xlim(0,1) # Change the legend title @@ -1133,10 +989,9 @@ scatter_compare_treatment <- ( ) ) + figure_theme + + ggplot2::coord_fixed(ratio = 1) # add y = x line + geom_abline(intercept = 0, slope = 1, linetype="dashed", color = "black") - # fix the coord - + ggplot2::coord_fixed(ratio = 1) ) scatter_compare_treatment diff --git a/figures/S7/figures/PBMCS7.png b/figures/S7/figures/PBMCS7.png index 80217aff4..820610767 100644 Binary files a/figures/S7/figures/PBMCS7.png and b/figures/S7/figures/PBMCS7.png differ diff --git a/figures/S7/notebooks/S7.ipynb b/figures/S7/notebooks/S7.ipynb index 4a33b4528..fea4d7b0a 100644 --- a/figures/S7/notebooks/S7.ipynb +++ b/figures/S7/notebooks/S7.ipynb @@ -17,6 +17,7 @@ "suppressPackageStartupMessages(suppressWarnings(library(RColorBrewer)))\n", "suppressPackageStartupMessages(suppressWarnings(library(patchwork)))\n", "suppressPackageStartupMessages(suppressWarnings(library(tidyr)))\n", + "suppressPackageStartupMessages(suppressWarnings(library(arrow)))\n", "\n", "# load in theme\n", "source(\"../../utils/figure_themes.r\")" @@ -50,44 +51,114 @@ "languageId": "r" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 6 \u00d7 5
Metadata_TreatmentMetadata_labelsmean_average_precisionshuffleddata_type
<chr><chr><dbl><chr><chr>
DMSO_0.100_%_DMSO_1.000_% Control0.9125000Non-shuffledMorphology
DMSO_0.100_%_Z-VAD-FMK_100.000_uMControl0.9097222Non-shuffledMorphology
DMSO_0.100_%_Z-VAD-FMK_30.000_uM Control0.8750000Non-shuffledMorphology
Disulfiram_0.100_uM_DMSO_0.025_% Control0.4178662Non-shuffledMorphology
Disulfiram_1.000_uM_DMSO_0.025_% Control0.4313672Non-shuffledMorphology
Disulfiram_2.500_uM_DMSO_0.025_% Control0.4289863Non-shuffledMorphology
\n" + ], + "text/latex": [ + "A tibble: 6 \u00d7 5\n", + "\\begin{tabular}{lllll}\n", + " Metadata\\_Treatment & Metadata\\_labels & mean\\_average\\_precision & shuffled & data\\_type\\\\\n", + " & & & & \\\\\n", + "\\hline\n", + "\t DMSO\\_0.100\\_\\%\\_DMSO\\_1.000\\_\\% & Control & 0.9125000 & Non-shuffled & Morphology\\\\\n", + "\t DMSO\\_0.100\\_\\%\\_Z-VAD-FMK\\_100.000\\_uM & Control & 0.9097222 & Non-shuffled & Morphology\\\\\n", + "\t DMSO\\_0.100\\_\\%\\_Z-VAD-FMK\\_30.000\\_uM & Control & 0.8750000 & Non-shuffled & Morphology\\\\\n", + "\t Disulfiram\\_0.100\\_uM\\_DMSO\\_0.025\\_\\% & Control & 0.4178662 & Non-shuffled & Morphology\\\\\n", + "\t Disulfiram\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & Control & 0.4313672 & Non-shuffled & Morphology\\\\\n", + "\t Disulfiram\\_2.500\\_uM\\_DMSO\\_0.025\\_\\% & Control & 0.4289863 & Non-shuffled & Morphology\\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "A tibble: 6 \u00d7 5\n", + "\n", + "| Metadata_Treatment <chr> | Metadata_labels <chr> | mean_average_precision <dbl> | shuffled <chr> | data_type <chr> |\n", + "|---|---|---|---|---|\n", + "| DMSO_0.100_%_DMSO_1.000_% | Control | 0.9125000 | Non-shuffled | Morphology |\n", + "| DMSO_0.100_%_Z-VAD-FMK_100.000_uM | Control | 0.9097222 | Non-shuffled | Morphology |\n", + "| DMSO_0.100_%_Z-VAD-FMK_30.000_uM | Control | 0.8750000 | Non-shuffled | Morphology |\n", + "| Disulfiram_0.100_uM_DMSO_0.025_% | Control | 0.4178662 | Non-shuffled | Morphology |\n", + "| Disulfiram_1.000_uM_DMSO_0.025_% | Control | 0.4313672 | Non-shuffled | Morphology |\n", + "| Disulfiram_2.500_uM_DMSO_0.025_% | Control | 0.4289863 | Non-shuffled | Morphology |\n", + "\n" + ], + "text/plain": [ + " Metadata_Treatment Metadata_labels mean_average_precision\n", + "1 DMSO_0.100_%_DMSO_1.000_% Control 0.9125000 \n", + "2 DMSO_0.100_%_Z-VAD-FMK_100.000_uM Control 0.9097222 \n", + "3 DMSO_0.100_%_Z-VAD-FMK_30.000_uM Control 0.8750000 \n", + "4 Disulfiram_0.100_uM_DMSO_0.025_% Control 0.4178662 \n", + "5 Disulfiram_1.000_uM_DMSO_0.025_% Control 0.4313672 \n", + "6 Disulfiram_2.500_uM_DMSO_0.025_% Control 0.4289863 \n", + " shuffled data_type \n", + "1 Non-shuffled Morphology\n", + "2 Non-shuffled Morphology\n", + "3 Non-shuffled Morphology\n", + "4 Non-shuffled Morphology\n", + "5 Non-shuffled Morphology\n", + "6 Non-shuffled Morphology" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set path to the data morphology\n", - "# class\n", - "df_morphology_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"aggregate_mAPs\",\"morphology\",\"mAP_scores_class.csv\")\n", - "reg_df_morphology_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_regular_class.csv\")\n", - "shuffled_morphology_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_shuffled_feature_space_class.csv\")\n", - "# treatment \n", - "treatment_df_morphology_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"aggregate_mAPs\",\"morphology\",\"mAP_scores_treatment.csv\")\n", - "reg_df_morphology_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_regular_treatment.csv\")\n", - "shuffled_morphology_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"mAP_scores_shuffled_feature_space_treatment.csv\")\n", "\n", + "morphology_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"activity_map.parquet\")\n", + "shuffled_morphology_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"morphology\",\"activity_map_shuffled.parquet\")\n", "# set path to the secretome data\n", - "# class\n", - "df_secretome_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"aggregate_mAPs\",\"secretome\",\"mAP_scores_class.csv\")\n", - "reg_df_secretome_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_regular_class.csv\")\n", - "shuffled_secretome_class_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_shuffled_feature_space_class.csv\")\n", - "# treatment\n", - "treatment_df_secretome_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"aggregate_mAPs\",\"secretome\",\"mAP_scores_treatment.csv\")\n", - "reg_df_secretome_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_regular_treatment.csv\")\n", - "shuffled_secretome_treatment_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"mAP_scores_shuffled_feature_space_treatment.csv\")\n", "\n", - "# read in the data\n", - "df_morphology_class <- read.csv(df_morphology_class_path)\n", - "reg_df_morphology_class <- read.csv(reg_df_morphology_class_path)\n", - "shuffled_morphology_class <- read.csv(shuffled_morphology_class_path)\n", + "secretome_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"activity_map.parquet\")\n", + "shuffled_secretome_path <- file.path(\"..\",\"..\",\"..\",\"9.mAP\",\"data\",\"processed\",\"mAP_scores\",\"secretome\",\"activity_map_shuffled.parquet\")\n", "\n", - "df_morphology_treatment <- read.csv(treatment_df_morphology_treatment_path)\n", - "reg_df_morphology_treatment <- read.csv(reg_df_morphology_treatment_path)\n", - "shuffled_morphology_treatment <- read.csv(shuffled_morphology_treatment_path)\n", + "df_morphology <- arrow::read_parquet(morphology_path) %>% \n", + " dplyr::mutate(shuffled = \"Non-shuffled\") %>%\n", + " dplyr::mutate(data_type = \"Morphology\") %>%\n", + " # rename the mean_average_precision column to specifcy morphology\n", + " # drop unnecessary columns\n", + " dplyr::select(-c(\"Metadata_reference_index\", \"indices\", \"p_value\", \"corrected_p_value\", \"below_p\", \"below_corrected_p\",\"-log10(p-value)\"))\t\n", "\n", - "df_secretome_class <- read.csv(df_secretome_class_path)\n", - "reg_df_secretome_class <- read.csv(reg_df_secretome_class_path)\n", - "shuffled_secretome_class <- read.csv(shuffled_secretome_class_path)\n", + "df_shuffled_morphology <- arrow::read_parquet(shuffled_morphology_path) %>%\n", + " dplyr::mutate(shuffled = \"Shuffled\") %>%\n", + " dplyr::mutate(data_type = \"Morphology\") %>%\n", + " # rename the mean_average_precision column to specifcy morphology\n", + " dplyr::select(-c(\"Metadata_reference_index\", \"indices\", \"p_value\", \"corrected_p_value\", \"below_p\", \"below_corrected_p\",\"-log10(p-value)\"))\t\n", "\n", - "df_secretome_treatment <- read.csv(treatment_df_secretome_treatment_path)\n", - "reg_df_secretome_treatment <- read.csv(reg_df_secretome_treatment_path)\n", - "shuffled_secretome_treatment <- read.csv(shuffled_secretome_treatment_path)" + "\n", + "df_secretome <- arrow::read_parquet(secretome_path) %>%\n", + " dplyr::mutate(shuffled = \"Non-shuffled\") %>%\n", + " dplyr::mutate(data_type = \"Secretome\") %>%\n", + " # rename the mean_average_precision column to specifcy secretome\n", + " dplyr::select(-c(\"Metadata_reference_index\", \"indices\", \"p_value\", \"corrected_p_value\", \"below_p\", \"below_corrected_p\",\"-log10(p-value)\"))\t\n", + "\n", + "\n", + "df_shuffled_secretome <- arrow::read_parquet(shuffled_secretome_path) %>%\n", + " dplyr::mutate(shuffled = \"Shuffled\") %>%\n", + " dplyr::mutate(data_type = \"Secretome\") %>%\n", + " # rename the mean_average_precision column to specifcy secretome\n", + " dplyr::select(-c(\"Metadata_reference_index\", \"indices\", \"p_value\", \"corrected_p_value\", \"below_p\", \"below_corrected_p\",\"-log10(p-value)\"))\t\n", + "\n", + "df <- dplyr::bind_rows(df_morphology, df_shuffled_morphology, df_secretome, df_shuffled_secretome)\n", + "head(df)" ] }, { @@ -166,36 +237,17 @@ }, "outputs": [], "source": [ - "# declare the shuffled column as a factor\n", - "# replace the values in the shuffled column\n", - "# declare the shuffled column as a factor\n", - "# replace the values in the shuffled column\n", - "df_morphology_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", df_morphology_class$shuffled)\n", - "df_morphology_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", df_morphology_class$shuffled)\n", - "df_morphology_class$shuffled <- factor(df_morphology_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "df_morphology_class$Metadata_labels <- factor(df_morphology_class$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", - "\n", - "df_secretome_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", df_secretome_class$shuffled)\n", - "df_secretome_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", df_secretome_class$shuffled)\n", - "df_secretome_class$shuffled <- factor(df_secretome_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "df_secretome_class$Metadata_labels <- factor(df_secretome_class$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", - "\n", - "df_morphology_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", df_morphology_treatment$shuffled)\n", - "df_morphology_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", df_morphology_treatment$shuffled)\n", - "df_morphology_treatment$shuffled <- factor(df_morphology_treatment$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)\n", - "\n", - "df_secretome_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", df_secretome_treatment$shuffled)\n", - "df_secretome_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", df_secretome_treatment$shuffled)\n", - "df_secretome_treatment$shuffled <- factor(df_secretome_treatment$shuffled, levels = c(\"Non-shuffled\", \"Shuffled\"))\n", - "df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Clean the single well data" + "# split out the morphology and secretome data\n", + "morphology_data <- df %>% dplyr::filter(data_type == \"Morphology\")\n", + "secretome_data <- df %>% dplyr::filter(data_type == \"Secretome\")\n", + "# rename the mean_average_precision column to specifcy morphology\n", + "morphology_data <- morphology_data %>% dplyr::rename(mAP_moprhology = mean_average_precision)\n", + "secretome_data <- secretome_data %>% dplyr::rename(mAP_secretome = mean_average_precision)\n", + "# drop the data_type column\n", + "morphology_data <- morphology_data %>% dplyr::select(-data_type)\n", + "secretome_data <- secretome_data %>% dplyr::select(-data_type)\n", + "# merge the data together to plot \n", + "df <- merge(morphology_data, secretome_data,by = c(\"Metadata_Treatment\", \"Metadata_labels\", \"shuffled\"))\n" ] }, { @@ -208,30 +260,8 @@ }, "outputs": [], "source": [ - "# combine the dataframes\n", - "all_df_morphology_class <- rbind(reg_df_morphology_class, shuffled_morphology_class)\n", - "all_df_morphology_treatment <- rbind(reg_df_morphology_treatment, shuffled_morphology_treatment)\n", - "all_df_secretome_class <- rbind(reg_df_secretome_class, shuffled_secretome_class)\n", - "all_df_secretome_treatment <- rbind(reg_df_secretome_treatment, shuffled_secretome_treatment)\n", - "\n", - "all_df_morphology_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_morphology_class$shuffled)\n", - "all_df_morphology_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_morphology_class$shuffled)\n", - "all_df_morphology_class$shuffled <- factor(all_df_morphology_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_morphology_class$Metadata_labels <- factor(all_df_morphology_class$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", - "\n", - "all_df_secretome_class$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_secretome_class$shuffled)\n", - "all_df_secretome_class$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_secretome_class$shuffled)\n", - "all_df_secretome_class$shuffled <- factor(all_df_secretome_class$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "\n", - "all_df_morphology_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_morphology_treatment$shuffled)\n", - "all_df_morphology_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_morphology_treatment$shuffled)\n", - "all_df_morphology_treatment$shuffled <- factor(all_df_morphology_treatment$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)\n", - "\n", - "all_df_secretome_treatment$shuffled <- gsub(\"shuffled\", \"Shuffled\", all_df_secretome_treatment$shuffled)\n", - "all_df_secretome_treatment$shuffled <- gsub(\"non-Shuffled\", \"Non-shuffled\", all_df_secretome_treatment$shuffled)\n", - "all_df_secretome_treatment$shuffled <- factor(all_df_secretome_treatment$shuffled, levels = c( \"Non-shuffled\", \"Shuffled\"))\n", - "all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list)" + "df$Metadata_labels <- factor(df$Metadata_labels, levels = c(\"Control\", \"Apoptosis\", \"Pyroptosis\"))\n", + "df$Metadata_Treatment <- factor(df$Metadata_Treatment, levels =levels_list)" ] }, { @@ -249,527 +279,6 @@ "languageId": "r" } }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 \u00d7 4
shuffledMetadata_labelsmorphology_apsecretome_ap
<fct><fct><dbl><dbl>
1Non-shuffledApoptosis0.54221761.0000000
2Non-shuffledApoptosis0.54221760.4508829
3Non-shuffledApoptosis0.54221761.0000000
4Non-shuffledApoptosis0.54221760.5267858
5Non-shuffledApoptosis0.54221761.0000000
6Non-shuffledApoptosis0.54221761.0000000
\n" - ], - "text/latex": [ - "A data.frame: 6 \u00d7 4\n", - "\\begin{tabular}{r|llll}\n", - " & shuffled & Metadata\\_labels & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & Apoptosis & 0.5422176 & 1.0000000\\\\\n", - "\t2 & Non-shuffled & Apoptosis & 0.5422176 & 0.4508829\\\\\n", - "\t3 & Non-shuffled & Apoptosis & 0.5422176 & 1.0000000\\\\\n", - "\t4 & Non-shuffled & Apoptosis & 0.5422176 & 0.5267858\\\\\n", - "\t5 & Non-shuffled & Apoptosis & 0.5422176 & 1.0000000\\\\\n", - "\t6 & Non-shuffled & Apoptosis & 0.5422176 & 1.0000000\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 \u00d7 4\n", - "\n", - "| | shuffled <fct> | Metadata_labels <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Apoptosis | 0.5422176 | 1.0000000 |\n", - "| 2 | Non-shuffled | Apoptosis | 0.5422176 | 0.4508829 |\n", - "| 3 | Non-shuffled | Apoptosis | 0.5422176 | 1.0000000 |\n", - "| 4 | Non-shuffled | Apoptosis | 0.5422176 | 0.5267858 |\n", - "| 5 | Non-shuffled | Apoptosis | 0.5422176 | 1.0000000 |\n", - "| 6 | Non-shuffled | Apoptosis | 0.5422176 | 1.0000000 |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels morphology_ap secretome_ap\n", - "1 Non-shuffled Apoptosis 0.5422176 1.0000000 \n", - "2 Non-shuffled Apoptosis 0.5422176 0.4508829 \n", - "3 Non-shuffled Apoptosis 0.5422176 1.0000000 \n", - "4 Non-shuffled Apoptosis 0.5422176 0.5267858 \n", - "5 Non-shuffled Apoptosis 0.5422176 1.0000000 \n", - "6 Non-shuffled Apoptosis 0.5422176 1.0000000 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# cobine the dfs\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_morphology_class <- all_df_morphology_class[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\")]\n", - "# rename the average_precision column to moprhology_ap\n", - "colnames(subset_morphology_class)[colnames(subset_morphology_class)==\"average_precision\"] <- \"morphology_ap\"\n", - "\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_secretome_class <- all_df_secretome_class[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\")]\n", - "# rename the average_precision column to secretome_ap\n", - "colnames(subset_secretome_class)[colnames(subset_secretome_class)==\"average_precision\"] <- \"secretome_ap\"\n", - "\n", - "# merge the dataframes\n", - "merged_df <- merge(subset_morphology_class, subset_secretome_class, by=c(\"shuffled\", \"Metadata_labels\"))\n", - "head(merged_df)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 \u00d7 5
shuffledMetadata_labelsmorphology_apsecretome_apgroup
<fct><fct><dbl><dbl><fct>
Non-shuffledControl 0.76991370.9708437NA
Shuffled Control 0.71515720.7235857NA
Non-shuffledApoptosis 0.52280630.8646785Non-shuffled\n", - "Apoptosis
Shuffled Apoptosis 0.13028980.1162887NA
Non-shuffledPyroptosis0.85798150.9357028NA
Shuffled Pyroptosis0.71187470.7089461NA
\n" - ], - "text/latex": [ - "A data.frame: 6 \u00d7 5\n", - "\\begin{tabular}{lllll}\n", - " shuffled & Metadata\\_labels & morphology\\_ap & secretome\\_ap & group\\\\\n", - " & & & & \\\\\n", - "\\hline\n", - "\t Non-shuffled & Control & 0.7699137 & 0.9708437 & NA \\\\\n", - "\t Shuffled & Control & 0.7151572 & 0.7235857 & NA \\\\\n", - "\t Non-shuffled & Apoptosis & 0.5228063 & 0.8646785 & Non-shuffled\n", - "Apoptosis\\\\\n", - "\t Shuffled & Apoptosis & 0.1302898 & 0.1162887 & NA \\\\\n", - "\t Non-shuffled & Pyroptosis & 0.8579815 & 0.9357028 & NA \\\\\n", - "\t Shuffled & Pyroptosis & 0.7118747 & 0.7089461 & NA \\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 \u00d7 5\n", - "\n", - "| shuffled <fct> | Metadata_labels <fct> | morphology_ap <dbl> | secretome_ap <dbl> | group <fct> |\n", - "|---|---|---|---|---|\n", - "| Non-shuffled | Control | 0.7699137 | 0.9708437 | NA |\n", - "| Shuffled | Control | 0.7151572 | 0.7235857 | NA |\n", - "| Non-shuffled | Apoptosis | 0.5228063 | 0.8646785 | Non-shuffled\n", - "Apoptosis |\n", - "| Shuffled | Apoptosis | 0.1302898 | 0.1162887 | NA |\n", - "| Non-shuffled | Pyroptosis | 0.8579815 | 0.9357028 | NA |\n", - "| Shuffled | Pyroptosis | 0.7118747 | 0.7089461 | NA |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels morphology_ap secretome_ap\n", - "1 Non-shuffled Control 0.7699137 0.9708437 \n", - "2 Shuffled Control 0.7151572 0.7235857 \n", - "3 Non-shuffled Apoptosis 0.5228063 0.8646785 \n", - "4 Shuffled Apoptosis 0.1302898 0.1162887 \n", - "5 Non-shuffled Pyroptosis 0.8579815 0.9357028 \n", - "6 Shuffled Pyroptosis 0.7118747 0.7089461 \n", - " group \n", - "1 NA \n", - "2 NA \n", - "3 Non-shuffled\\nApoptosis\n", - "4 NA \n", - "5 NA \n", - "6 NA " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# aggregate the data by shuffled and Metadata_labels\n", - "merged_agg <- aggregate(. ~ shuffled + Metadata_labels, data=merged_df, FUN=mean)\n", - "# combine the shuffled and Metadata_labels columns\n", - "merged_agg$group <- paste(merged_agg$shuffled, merged_agg$Metadata_labels, sep=\"_\")\n", - "# change the text in the group column\n", - "merged_agg$group <- gsub(\"Non-shuffled Control\", \"Non-shuffled\\nControl\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Control\", \"Shuffled\\nControl\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Non-shuffled_Apoptosis\", \"Non-shuffled\\nApoptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Apoptosis\", \"Shuffled\\nApoptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Non-shuffled Pyroptosis\", \"Non-shuffled\\nPyroptosis\", merged_agg$group)\n", - "merged_agg$group <- gsub(\"Shuffled Pyroptosis\", \"Shuffled\\nPyroptosis\", merged_agg$group)\n", - "# make the group column a factor\n", - "merged_agg$group <- factor(\n", - " merged_agg$group, \n", - " levels = c(\n", - " \"Non-shuffled\\nControl\", \n", - " \"Shuffled features\\nControl\", \n", - " \"Shuffled phenotypes\\nControl\", \n", - "\n", - " \"Non-shuffled\\nApoptosis\", \n", - " \"Shuffled features\\nApoptosis\", \n", - " \"Shuffled phenotypes\\nApoptosis\",\n", - " \n", - " \"Non-shuffled\\nPyroptosis\",\n", - " \"Shuffled features\\nPyroptosis\", \n", - " \"Shuffled phenotypes\\nPyroptosis\"))\n", - "\n", - "merged_agg" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 360, - "width": 480 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "width <- 8\n", - "height <- 6\n", - "options(repr.plot.width=width, repr.plot.height=height)\n", - "# plot the data\n", - "scatter_compare <- (\n", - " ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled))\n", - " + geom_point(size=3, alpha=1)\n", - " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", - " + theme_bw()\n", - " + ggtitle(\"Comparison of mAP scores\")\n", - " + ylim(0,1)\n", - " + xlim(0,1)\n", - " # Change the legend title\n", - " # change the legend shape\n", - " + scale_shape_manual(\n", - " name=\"Shuffle type\",\n", - " labels=c(\n", - " \"Non-shuffled\", \n", - " \"Shuffled features\", \n", - " \"Shuffled phenotypes\"\n", - " ),\n", - " values=c(19, 17, 15)\n", - " )\n", - " + scale_color_manual(\n", - " name=\"Class\",\n", - " labels=c(\n", - " \"Control\", \n", - " \"Apoptosis\", \n", - " \"Pyroptosis\"\n", - " ),\n", - " values=c(\n", - " brewer.pal(3, \"Dark2\")[2],\n", - " brewer.pal(3, \"Dark2\")[1],\n", - " brewer.pal(3, \"Dark2\")[3]\n", - " )\n", - ")\n", - " + figure_theme\n", - " # add y = x line\n", - " + geom_abline(intercept = 0, slope = 1, linetype=\"dashed\")\n", - "\n", - ")\n", - "scatter_compare" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## mAP Scatter compare plot treatemnts\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 \u00d7 5
shuffledMetadata_labelsoneb_Metadata_Treatment_Dose_Inhibitor_Dosemorphology_apsecretome_ap
<fct><chr><fct><dbl><dbl>
1Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
2Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
3Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
4Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
5Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
6Non-shuffledApoptosisThapsigargin_1.000_uM_DMSO_0.025_%0.76666671
\n" - ], - "text/latex": [ - "A data.frame: 6 \u00d7 5\n", - "\\begin{tabular}{r|lllll}\n", - " & shuffled & Metadata\\_labels & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t2 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t3 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t4 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t5 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\t6 & Non-shuffled & Apoptosis & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & 0.7666667 & 1\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 \u00d7 5\n", - "\n", - "| | shuffled <fct> | Metadata_labels <chr> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 2 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 3 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 4 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 5 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "| 6 | Non-shuffled | Apoptosis | Thapsigargin_1.000_uM_DMSO_0.025_% | 0.7666667 | 1 |\n", - "\n" - ], - "text/plain": [ - " shuffled Metadata_labels oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "1 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "2 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "3 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "4 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "5 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - "6 Non-shuffled Apoptosis Thapsigargin_1.000_uM_DMSO_0.025_% \n", - " morphology_ap secretome_ap\n", - "1 0.7666667 1 \n", - "2 0.7666667 1 \n", - "3 0.7666667 1 \n", - "4 0.7666667 1 \n", - "5 0.7666667 1 \n", - "6 0.7666667 1 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# cobine the dfs\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_morphology_treatment <- all_df_morphology_treatment[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\",\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\")]\n", - "# rename the average_precision column to moprhology_ap\n", - "colnames(subset_morphology_treatment)[colnames(subset_morphology_treatment)==\"average_precision\"] <- \"morphology_ap\"\n", - "\n", - "# get the average precision, shuffled, and Metadata_labels columns by name\n", - "subset_secretome_treatment <- all_df_secretome_treatment[,c(\"average_precision\", \"shuffled\", \"Metadata_labels\",\"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\")]\n", - "# rename the average_precision column to secretome_ap\n", - "colnames(subset_secretome_treatment)[colnames(subset_secretome_treatment)==\"average_precision\"] <- \"secretome_ap\"\n", - "\n", - "# merge the dataframes\n", - "merged_df <- merge(subset_morphology_treatment, subset_secretome_treatment, by=c(\"shuffled\", \"Metadata_labels\", \"oneb_Metadata_Treatment_Dose_Inhibitor_Dose\"))\n", - "head(merged_df)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": { - "image/png": { - "height": 360, - "width": 480 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled\n", - "merged_agg <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels, data=merged_df, FUN=mean)\n", - "# scatter plot\n", - "scatter_compare_treatment <- (\n", - " ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled))\n", - " + geom_point(size=3, alpha=0.5)\n", - " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", - " + theme_bw()\n", - " + ggtitle(\"Comparison of mAP scores\")\n", - " + ylim(0,1)\n", - " + xlim(0,1)\n", - " # Change the legend title\n", - " # change the legend shape\n", - " + scale_shape_manual(\n", - " name=\"Shuffle type\",\n", - " labels=c(\n", - " \"Non-shuffled\", \n", - " \"Shuffled features\", \n", - " \"Shuffled phenotypes\"\n", - " ),\n", - " values=c(19, 17, 15)\n", - " )\n", - " + scale_color_manual(\n", - " name=\"Class\",\n", - " labels=c(\n", - " \"Control\", \n", - " \"Apoptosis\", \n", - " \"Pyroptosis\"\n", - " ),\n", - " values=c(\n", - " brewer.pal(3, \"Dark2\")[2],\n", - " brewer.pal(3, \"Dark2\")[1],\n", - " brewer.pal(3, \"Dark2\")[3]\n", - " )\n", - ")\n", - " + figure_theme\n", - " # add y = x line\n", - " + geom_abline(intercept = 0, slope = 1, linetype=\"dashed\", color = \"black\")\n", - " # fix coordiantes\n", - " + ggplot2::coord_fixed()\n", - "\n", - ")\n", - "scatter_compare_treatment" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 \u00d7 5
shuffledoneb_Metadata_Treatment_Dose_Inhibitor_DoseMetadata_labelsmorphology_apsecretome_ap
<fct><fct><chr><dbl><dbl>
1Non-shuffledThapsigargin_1.000_uM_DMSO_0.025_% Apoptosis0.65297621.0000000
2Shuffled Thapsigargin_1.000_uM_DMSO_0.025_% Apoptosis0.41736111.0000000
3Non-shuffledThapsigargin_10.000_uM_DMSO_0.025_%Apoptosis0.97916671.0000000
4Shuffled Thapsigargin_10.000_uM_DMSO_0.025_%Apoptosis0.41269841.0000000
5Non-shuffledMedia Control 0.58629220.2903931
6Shuffled Media Control 0.51995080.1724887
\n" - ], - "text/latex": [ - "A data.frame: 6 \u00d7 5\n", - "\\begin{tabular}{r|lllll}\n", - " & shuffled & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & Metadata\\_labels & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & Apoptosis & 0.6529762 & 1.0000000\\\\\n", - "\t2 & Shuffled & Thapsigargin\\_1.000\\_uM\\_DMSO\\_0.025\\_\\% & Apoptosis & 0.4173611 & 1.0000000\\\\\n", - "\t3 & Non-shuffled & Thapsigargin\\_10.000\\_uM\\_DMSO\\_0.025\\_\\% & Apoptosis & 0.9791667 & 1.0000000\\\\\n", - "\t4 & Shuffled & Thapsigargin\\_10.000\\_uM\\_DMSO\\_0.025\\_\\% & Apoptosis & 0.4126984 & 1.0000000\\\\\n", - "\t5 & Non-shuffled & Media & Control & 0.5862922 & 0.2903931\\\\\n", - "\t6 & Shuffled & Media & Control & 0.5199508 & 0.1724887\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 \u00d7 5\n", - "\n", - "| | shuffled <fct> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <fct> | Metadata_labels <chr> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Thapsigargin_1.000_uM_DMSO_0.025_% | Apoptosis | 0.6529762 | 1.0000000 |\n", - "| 2 | Shuffled | Thapsigargin_1.000_uM_DMSO_0.025_% | Apoptosis | 0.4173611 | 1.0000000 |\n", - "| 3 | Non-shuffled | Thapsigargin_10.000_uM_DMSO_0.025_% | Apoptosis | 0.9791667 | 1.0000000 |\n", - "| 4 | Shuffled | Thapsigargin_10.000_uM_DMSO_0.025_% | Apoptosis | 0.4126984 | 1.0000000 |\n", - "| 5 | Non-shuffled | Media | Control | 0.5862922 | 0.2903931 |\n", - "| 6 | Shuffled | Media | Control | 0.5199508 | 0.1724887 |\n", - "\n" - ], - "text/plain": [ - " shuffled oneb_Metadata_Treatment_Dose_Inhibitor_Dose Metadata_labels\n", - "1 Non-shuffled Thapsigargin_1.000_uM_DMSO_0.025_% Apoptosis \n", - "2 Shuffled Thapsigargin_1.000_uM_DMSO_0.025_% Apoptosis \n", - "3 Non-shuffled Thapsigargin_10.000_uM_DMSO_0.025_% Apoptosis \n", - "4 Shuffled Thapsigargin_10.000_uM_DMSO_0.025_% Apoptosis \n", - "5 Non-shuffled Media Control \n", - "6 Shuffled Media Control \n", - " morphology_ap secretome_ap\n", - "1 0.6529762 1.0000000 \n", - "2 0.4173611 1.0000000 \n", - "3 0.9791667 1.0000000 \n", - "4 0.4126984 1.0000000 \n", - "5 0.5862922 0.2903931 \n", - "6 0.5199508 0.1724887 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "head(merged_agg)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "vscode": { - "languageId": "r" - } - }, "outputs": [ { "data": { @@ -779,80 +288,80 @@ ".list-inline>li {display: inline-block}\n", ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n", "\n", - "
  1. 'Thapsigargin 1.0 uM'
  2. 'Thapsigargin 10.0 uM'
  3. 'Disulfiram 0.1 uM'
  4. 'Disulfiram 1.0 uM'
  5. 'Disulfiram 2.5 uM'
  6. 'DMSO 0.1%'
  7. 'H2O2 100.0 nM'
  8. 'H2O2 100.0 uM'
  9. 'LPS 10.0 ug/ml'
  10. 'LPS 1.0 ug/ml + Nigericin 10.0 uM'
  11. NA
  12. 'Topotecan 10.0 nM'
  13. 'Topotecan 20.0 nM'
  14. 'Topotecan 5.0 nM'
  15. 'Flagellin 0.1 ug/ml'
  16. 'Flagellin 1.0 ug/ml'
  17. 'LPS 0.01 ug/ml'
  18. 'LPS 0.1 ug/ml'
  19. 'LPS 1.0 ug/ml'
  20. 'LPS 100.0 ug/ml'
  21. 'LPS 1.0 ug/ml + Nigericin 1.0 uM'
  22. 'LPS 1.0 ug/ml + Nigericin 3.0 uM'
  23. 'LPS 100.0 ug/ml + Nigericin 1.0 uM'
  24. 'LPS 100.0 ug/ml + Nigericin 10.0 uM'
  25. 'LPS 100.0 ug/ml + Nigericin 3.0 uM'
\n" + "
  1. 'Disulfiram 0.1 uM'
  2. 'Disulfiram 1.0 uM'
  3. 'Disulfiram 2.5 uM'
  4. 'DMSO 0.1%'
  5. 'Flagellin 0.1 ug/ml'
  6. 'Flagellin 1.0 ug/ml'
  7. 'H2O2 100.0 nM'
  8. 'H2O2 100.0 uM'
  9. 'LPS 0.01 ug/ml'
  10. 'LPS 0.1 ug/ml'
  11. 'LPS 1.0 ug/ml'
  12. 'LPS 10.0 ug/ml'
  13. 'LPS 100.0 ug/ml'
  14. 'LPS 1.0 ug/ml + Nigericin 1.0 uM'
  15. 'LPS 1.0 ug/ml + Nigericin 10.0 uM'
  16. 'LPS 1.0 ug/ml + Nigericin 3.0 uM'
  17. 'LPS 100.0 ug/ml + Nigericin 1.0 uM'
  18. 'LPS 100.0 ug/ml + Nigericin 10.0 uM'
  19. 'LPS 100.0 ug/ml + Nigericin 3.0 uM'
  20. NA
  21. 'Thapsigargin 1.0 uM'
  22. 'Thapsigargin 10.0 uM'
  23. 'Topotecan 10.0 nM'
  24. 'Topotecan 20.0 nM'
  25. 'Topotecan 5.0 nM'
\n" ], "text/latex": [ "\\begin{enumerate*}\n", - "\\item 'Thapsigargin 1.0 uM'\n", - "\\item 'Thapsigargin 10.0 uM'\n", "\\item 'Disulfiram 0.1 uM'\n", "\\item 'Disulfiram 1.0 uM'\n", "\\item 'Disulfiram 2.5 uM'\n", "\\item 'DMSO 0.1\\%'\n", - "\\item 'H2O2 100.0 nM'\n", - "\\item 'H2O2 100.0 uM'\n", - "\\item 'LPS 10.0 ug/ml'\n", - "\\item 'LPS 1.0 ug/ml + Nigericin 10.0 uM'\n", - "\\item NA\n", - "\\item 'Topotecan 10.0 nM'\n", - "\\item 'Topotecan 20.0 nM'\n", - "\\item 'Topotecan 5.0 nM'\n", "\\item 'Flagellin 0.1 ug/ml'\n", "\\item 'Flagellin 1.0 ug/ml'\n", + "\\item 'H2O2 100.0 nM'\n", + "\\item 'H2O2 100.0 uM'\n", "\\item 'LPS 0.01 ug/ml'\n", "\\item 'LPS 0.1 ug/ml'\n", "\\item 'LPS 1.0 ug/ml'\n", + "\\item 'LPS 10.0 ug/ml'\n", "\\item 'LPS 100.0 ug/ml'\n", "\\item 'LPS 1.0 ug/ml + Nigericin 1.0 uM'\n", + "\\item 'LPS 1.0 ug/ml + Nigericin 10.0 uM'\n", "\\item 'LPS 1.0 ug/ml + Nigericin 3.0 uM'\n", "\\item 'LPS 100.0 ug/ml + Nigericin 1.0 uM'\n", "\\item 'LPS 100.0 ug/ml + Nigericin 10.0 uM'\n", "\\item 'LPS 100.0 ug/ml + Nigericin 3.0 uM'\n", + "\\item NA\n", + "\\item 'Thapsigargin 1.0 uM'\n", + "\\item 'Thapsigargin 10.0 uM'\n", + "\\item 'Topotecan 10.0 nM'\n", + "\\item 'Topotecan 20.0 nM'\n", + "\\item 'Topotecan 5.0 nM'\n", "\\end{enumerate*}\n" ], "text/markdown": [ - "1. 'Thapsigargin 1.0 uM'\n", - "2. 'Thapsigargin 10.0 uM'\n", - "3. 'Disulfiram 0.1 uM'\n", - "4. 'Disulfiram 1.0 uM'\n", - "5. 'Disulfiram 2.5 uM'\n", - "6. 'DMSO 0.1%'\n", + "1. 'Disulfiram 0.1 uM'\n", + "2. 'Disulfiram 1.0 uM'\n", + "3. 'Disulfiram 2.5 uM'\n", + "4. 'DMSO 0.1%'\n", + "5. 'Flagellin 0.1 ug/ml'\n", + "6. 'Flagellin 1.0 ug/ml'\n", "7. 'H2O2 100.0 nM'\n", "8. 'H2O2 100.0 uM'\n", - "9. 'LPS 10.0 ug/ml'\n", - "10. 'LPS 1.0 ug/ml + Nigericin 10.0 uM'\n", - "11. NA\n", - "12. 'Topotecan 10.0 nM'\n", - "13. 'Topotecan 20.0 nM'\n", - "14. 'Topotecan 5.0 nM'\n", - "15. 'Flagellin 0.1 ug/ml'\n", - "16. 'Flagellin 1.0 ug/ml'\n", - "17. 'LPS 0.01 ug/ml'\n", - "18. 'LPS 0.1 ug/ml'\n", - "19. 'LPS 1.0 ug/ml'\n", - "20. 'LPS 100.0 ug/ml'\n", - "21. 'LPS 1.0 ug/ml + Nigericin 1.0 uM'\n", - "22. 'LPS 1.0 ug/ml + Nigericin 3.0 uM'\n", - "23. 'LPS 100.0 ug/ml + Nigericin 1.0 uM'\n", - "24. 'LPS 100.0 ug/ml + Nigericin 10.0 uM'\n", - "25. 'LPS 100.0 ug/ml + Nigericin 3.0 uM'\n", + "9. 'LPS 0.01 ug/ml'\n", + "10. 'LPS 0.1 ug/ml'\n", + "11. 'LPS 1.0 ug/ml'\n", + "12. 'LPS 10.0 ug/ml'\n", + "13. 'LPS 100.0 ug/ml'\n", + "14. 'LPS 1.0 ug/ml + Nigericin 1.0 uM'\n", + "15. 'LPS 1.0 ug/ml + Nigericin 10.0 uM'\n", + "16. 'LPS 1.0 ug/ml + Nigericin 3.0 uM'\n", + "17. 'LPS 100.0 ug/ml + Nigericin 1.0 uM'\n", + "18. 'LPS 100.0 ug/ml + Nigericin 10.0 uM'\n", + "19. 'LPS 100.0 ug/ml + Nigericin 3.0 uM'\n", + "20. NA\n", + "21. 'Thapsigargin 1.0 uM'\n", + "22. 'Thapsigargin 10.0 uM'\n", + "23. 'Topotecan 10.0 nM'\n", + "24. 'Topotecan 20.0 nM'\n", + "25. 'Topotecan 5.0 nM'\n", "\n", "\n" ], "text/plain": [ - " [1] \"Thapsigargin 1.0 uM\" \"Thapsigargin 10.0 uM\" \n", - " [3] \"Disulfiram 0.1 uM\" \"Disulfiram 1.0 uM\" \n", - " [5] \"Disulfiram 2.5 uM\" \"DMSO 0.1%\" \n", + " [1] \"Disulfiram 0.1 uM\" \"Disulfiram 1.0 uM\" \n", + " [3] \"Disulfiram 2.5 uM\" \"DMSO 0.1%\" \n", + " [5] \"Flagellin 0.1 ug/ml\" \"Flagellin 1.0 ug/ml\" \n", " [7] \"H2O2 100.0 nM\" \"H2O2 100.0 uM\" \n", - " [9] \"LPS 10.0 ug/ml\" \"LPS 1.0 ug/ml + Nigericin 10.0 uM\" \n", - "[11] NA \"Topotecan 10.0 nM\" \n", - "[13] \"Topotecan 20.0 nM\" \"Topotecan 5.0 nM\" \n", - "[15] \"Flagellin 0.1 ug/ml\" \"Flagellin 1.0 ug/ml\" \n", - "[17] \"LPS 0.01 ug/ml\" \"LPS 0.1 ug/ml\" \n", - "[19] \"LPS 1.0 ug/ml\" \"LPS 100.0 ug/ml\" \n", - "[21] \"LPS 1.0 ug/ml + Nigericin 1.0 uM\" \"LPS 1.0 ug/ml + Nigericin 3.0 uM\" \n", - "[23] \"LPS 100.0 ug/ml + Nigericin 1.0 uM\" \"LPS 100.0 ug/ml + Nigericin 10.0 uM\"\n", - "[25] \"LPS 100.0 ug/ml + Nigericin 3.0 uM\" " + " [9] \"LPS 0.01 ug/ml\" \"LPS 0.1 ug/ml\" \n", + "[11] \"LPS 1.0 ug/ml\" \"LPS 10.0 ug/ml\" \n", + "[13] \"LPS 100.0 ug/ml\" \"LPS 1.0 ug/ml + Nigericin 1.0 uM\" \n", + "[15] \"LPS 1.0 ug/ml + Nigericin 10.0 uM\" \"LPS 1.0 ug/ml + Nigericin 3.0 uM\" \n", + "[17] \"LPS 100.0 ug/ml + Nigericin 1.0 uM\" \"LPS 100.0 ug/ml + Nigericin 10.0 uM\"\n", + "[19] \"LPS 100.0 ug/ml + Nigericin 3.0 uM\" NA \n", + "[21] \"Thapsigargin 1.0 uM\" \"Thapsigargin 10.0 uM\" \n", + "[23] \"Topotecan 10.0 nM\" \"Topotecan 20.0 nM\" \n", + "[25] \"Topotecan 5.0 nM\" " ] }, "metadata": {}, @@ -866,7 +375,7 @@ ".list-inline>li {display: inline-block}\n", ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n", "\n", - "
  1. 'DMSO 0.025%'
  2. 'DMSO 1.0%'
  3. 'Z-VAD-FMK 100.0 uM'
  4. 'Z-VAD-FMK 30.0 uM'
  5. 'Disulfiram 1.0 uM'
  6. 'Media'
  7. 'Disulfiram 0.1 uM'
  8. 'Disulfiram 2.5 uM'
\n" + "
  1. 'DMSO 0.025%'
  2. 'DMSO 1.0%'
  3. 'Z-VAD-FMK 100.0 uM'
  4. 'Z-VAD-FMK 30.0 uM'
  5. 'Disulfiram 1.0 uM'
  6. 'Disulfiram 0.1 uM'
  7. 'Disulfiram 2.5 uM'
  8. 'Media'
\n" ], "text/latex": [ "\\begin{enumerate*}\n", @@ -875,9 +384,9 @@ "\\item 'Z-VAD-FMK 100.0 uM'\n", "\\item 'Z-VAD-FMK 30.0 uM'\n", "\\item 'Disulfiram 1.0 uM'\n", - "\\item 'Media'\n", "\\item 'Disulfiram 0.1 uM'\n", "\\item 'Disulfiram 2.5 uM'\n", + "\\item 'Media'\n", "\\end{enumerate*}\n" ], "text/markdown": [ @@ -886,16 +395,16 @@ "3. 'Z-VAD-FMK 100.0 uM'\n", "4. 'Z-VAD-FMK 30.0 uM'\n", "5. 'Disulfiram 1.0 uM'\n", - "6. 'Media'\n", - "7. 'Disulfiram 0.1 uM'\n", - "8. 'Disulfiram 2.5 uM'\n", + "6. 'Disulfiram 0.1 uM'\n", + "7. 'Disulfiram 2.5 uM'\n", + "8. 'Media'\n", "\n", "\n" ], "text/plain": [ "[1] \"DMSO 0.025%\" \"DMSO 1.0%\" \"Z-VAD-FMK 100.0 uM\"\n", - "[4] \"Z-VAD-FMK 30.0 uM\" \"Disulfiram 1.0 uM\" \"Media\" \n", - "[7] \"Disulfiram 0.1 uM\" \"Disulfiram 2.5 uM\" " + "[4] \"Z-VAD-FMK 30.0 uM\" \"Disulfiram 1.0 uM\" \"Disulfiram 0.1 uM\" \n", + "[7] \"Disulfiram 2.5 uM\" \"Media\" " ] }, "metadata": {}, @@ -907,62 +416,62 @@ "\n", "\n", "\n", - "\t\n", - "\t\n", + "\t\n", + "\t\n", "\n", "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", "\n", "
A data.frame: 6 \u00d7 7
shuffledMetadata_labelsoneb_Metadata_Treatment_Dose_Inhibitor_Doseinducerinhibitormorphology_apsecretome_ap
<fct><chr><chr><fct><fct><dbl><dbl>
Metadata_TreatmentinducerinhibitorMetadata_labelsshuffledmAP_moprhologymAP_secretome
<chr><fct><fct><fct><chr><dbl><dbl>
1Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.76666671
2Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.76666671
3Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.76666671
4Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.76666671
5Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.76666671
6Non-shuffledApoptosisThapsigargin 1.0 uM - DMSO 0.025%Thapsigargin 1.0 uMDMSO 0.025%0.76666671
1Disulfiram 0.1 uM - DMSO 0.025%Disulfiram 0.1 uMDMSO 0.025%Control Non-shuffled0.41786620.4012085
2Disulfiram 0.1 uM - DMSO 0.025%Disulfiram 0.1 uMDMSO 0.025%PyroptosisShuffled 0.36246690.1428571
3Disulfiram 1.0 uM - DMSO 0.025%Disulfiram 1.0 uMDMSO 0.025%Control Non-shuffled0.43136720.5312500
4Disulfiram 1.0 uM - DMSO 0.025%Disulfiram 1.0 uMDMSO 0.025%Control Shuffled 0.11805560.1555556
5Disulfiram 1.0 uM - DMSO 0.025%Disulfiram 1.0 uMDMSO 0.025%PyroptosisShuffled 0.75000000.1458333
6Disulfiram 2.5 uM - DMSO 0.025%Disulfiram 2.5 uMDMSO 0.025%Control Non-shuffled0.42898630.5597222
\n" ], "text/latex": [ "A data.frame: 6 \u00d7 7\n", "\\begin{tabular}{r|lllllll}\n", - " & shuffled & Metadata\\_labels & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & inducer & inhibitor & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & & & \\\\\n", + " & Metadata\\_Treatment & inducer & inhibitor & Metadata\\_labels & shuffled & mAP\\_moprhology & mAP\\_secretome\\\\\n", + " & & & & & & & \\\\\n", "\\hline\n", - "\t1 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7666667 & 1\\\\\n", - "\t2 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7666667 & 1\\\\\n", - "\t3 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7666667 & 1\\\\\n", - "\t4 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7666667 & 1\\\\\n", - "\t5 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7666667 & 1\\\\\n", - "\t6 & Non-shuffled & Apoptosis & Thapsigargin 1.0 uM - DMSO 0.025\\% & Thapsigargin 1.0 uM & DMSO 0.025\\% & 0.7666667 & 1\\\\\n", + "\t1 & Disulfiram 0.1 uM - DMSO 0.025\\% & Disulfiram 0.1 uM & DMSO 0.025\\% & Control & Non-shuffled & 0.4178662 & 0.4012085\\\\\n", + "\t2 & Disulfiram 0.1 uM - DMSO 0.025\\% & Disulfiram 0.1 uM & DMSO 0.025\\% & Pyroptosis & Shuffled & 0.3624669 & 0.1428571\\\\\n", + "\t3 & Disulfiram 1.0 uM - DMSO 0.025\\% & Disulfiram 1.0 uM & DMSO 0.025\\% & Control & Non-shuffled & 0.4313672 & 0.5312500\\\\\n", + "\t4 & Disulfiram 1.0 uM - DMSO 0.025\\% & Disulfiram 1.0 uM & DMSO 0.025\\% & Control & Shuffled & 0.1180556 & 0.1555556\\\\\n", + "\t5 & Disulfiram 1.0 uM - DMSO 0.025\\% & Disulfiram 1.0 uM & DMSO 0.025\\% & Pyroptosis & Shuffled & 0.7500000 & 0.1458333\\\\\n", + "\t6 & Disulfiram 2.5 uM - DMSO 0.025\\% & Disulfiram 2.5 uM & DMSO 0.025\\% & Control & Non-shuffled & 0.4289863 & 0.5597222\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A data.frame: 6 \u00d7 7\n", "\n", - "| | shuffled <fct> | Metadata_labels <chr> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <chr> | inducer <fct> | inhibitor <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", + "| | Metadata_Treatment <chr> | inducer <fct> | inhibitor <fct> | Metadata_labels <fct> | shuffled <chr> | mAP_moprhology <dbl> | mAP_secretome <dbl> |\n", "|---|---|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7666667 | 1 |\n", - "| 2 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7666667 | 1 |\n", - "| 3 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7666667 | 1 |\n", - "| 4 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7666667 | 1 |\n", - "| 5 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7666667 | 1 |\n", - "| 6 | Non-shuffled | Apoptosis | Thapsigargin 1.0 uM - DMSO 0.025% | Thapsigargin 1.0 uM | DMSO 0.025% | 0.7666667 | 1 |\n", + "| 1 | Disulfiram 0.1 uM - DMSO 0.025% | Disulfiram 0.1 uM | DMSO 0.025% | Control | Non-shuffled | 0.4178662 | 0.4012085 |\n", + "| 2 | Disulfiram 0.1 uM - DMSO 0.025% | Disulfiram 0.1 uM | DMSO 0.025% | Pyroptosis | Shuffled | 0.3624669 | 0.1428571 |\n", + "| 3 | Disulfiram 1.0 uM - DMSO 0.025% | Disulfiram 1.0 uM | DMSO 0.025% | Control | Non-shuffled | 0.4313672 | 0.5312500 |\n", + "| 4 | Disulfiram 1.0 uM - DMSO 0.025% | Disulfiram 1.0 uM | DMSO 0.025% | Control | Shuffled | 0.1180556 | 0.1555556 |\n", + "| 5 | Disulfiram 1.0 uM - DMSO 0.025% | Disulfiram 1.0 uM | DMSO 0.025% | Pyroptosis | Shuffled | 0.7500000 | 0.1458333 |\n", + "| 6 | Disulfiram 2.5 uM - DMSO 0.025% | Disulfiram 2.5 uM | DMSO 0.025% | Control | Non-shuffled | 0.4289863 | 0.5597222 |\n", "\n" ], "text/plain": [ - " shuffled Metadata_labels oneb_Metadata_Treatment_Dose_Inhibitor_Dose\n", - "1 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "2 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "3 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "4 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "5 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - "6 Non-shuffled Apoptosis Thapsigargin 1.0 uM - DMSO 0.025% \n", - " inducer inhibitor morphology_ap secretome_ap\n", - "1 Thapsigargin 1.0 uM DMSO 0.025% 0.7666667 1 \n", - "2 Thapsigargin 1.0 uM DMSO 0.025% 0.7666667 1 \n", - "3 Thapsigargin 1.0 uM DMSO 0.025% 0.7666667 1 \n", - "4 Thapsigargin 1.0 uM DMSO 0.025% 0.7666667 1 \n", - "5 Thapsigargin 1.0 uM DMSO 0.025% 0.7666667 1 \n", - "6 Thapsigargin 1.0 uM DMSO 0.025% 0.7666667 1 " + " Metadata_Treatment inducer inhibitor Metadata_labels\n", + "1 Disulfiram 0.1 uM - DMSO 0.025% Disulfiram 0.1 uM DMSO 0.025% Control \n", + "2 Disulfiram 0.1 uM - DMSO 0.025% Disulfiram 0.1 uM DMSO 0.025% Pyroptosis \n", + "3 Disulfiram 1.0 uM - DMSO 0.025% Disulfiram 1.0 uM DMSO 0.025% Control \n", + "4 Disulfiram 1.0 uM - DMSO 0.025% Disulfiram 1.0 uM DMSO 0.025% Control \n", + "5 Disulfiram 1.0 uM - DMSO 0.025% Disulfiram 1.0 uM DMSO 0.025% Pyroptosis \n", + "6 Disulfiram 2.5 uM - DMSO 0.025% Disulfiram 2.5 uM DMSO 0.025% Control \n", + " shuffled mAP_moprhology mAP_secretome\n", + "1 Non-shuffled 0.4178662 0.4012085 \n", + "2 Shuffled 0.3624669 0.1428571 \n", + "3 Non-shuffled 0.4313672 0.5312500 \n", + "4 Shuffled 0.1180556 0.1555556 \n", + "5 Shuffled 0.7500000 0.1458333 \n", + "6 Non-shuffled 0.4289863 0.5597222 " ] }, "metadata": {}, @@ -970,64 +479,64 @@ } ], "source": [ - "merged_df <- merged_df %>%\n", - " mutate(oneb_Metadata_Treatment_Dose_Inhibitor_Dose = case_when(\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_DMSO_0.025_%' ~ \"DMSO 0.1% - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_DMSO_1.000_%' ~ \"DMSO 0.1% - DMSO 1.0%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_Z-VAD-FMK_100.000_uM' ~ \"DMSO 0.1% - Z-VAD-FMK 100.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_Z-VAD-FMK_30.000_uM' ~ \"DMSO 0.1% - Z-VAD-FMK 30.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_DMSO_0.025_%' ~ \"Flagellin 1.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM' ~ \"Flagellin 1.0 ug/ml - Disulfiram 1.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_0.010_ug_per_ml_DMSO_0.025_%' ~ \"LPS 0.01 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_0.100_ug_per_ml_DMSO_0.025_%' ~ \"LPS 0.1 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_0.100_ug_per_ml_DMSO_0.0_%' ~ \"Flagellin 0.1 ug/ml - DMSO 0.0%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_0.100_ug_per_ml_DMSO_0.025_%' ~ \"Flagellin 0.1 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_0.100_uM_DMSO_0.025_%' ~ \"Disulfiram 0.1 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - Disulfiram 1.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - Z-VAD-FMK 100.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_1.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_DMSO_0.0_%' ~ \"Flagellin 1.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_1.000_uM_DMSO_0.025_%' ~ \"Disulfiram 1.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Thapsigargin_1.000_uM_DMSO_0.025_%' ~ \"Thapsigargin 1.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_10.000_nM_DMSO_0.025_%' ~ \"Topotecan 10.0 nM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 10.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_0.100_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 0.1 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_1.000_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 1.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_2.500_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 2.5 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM' ~ \"LPS 10.0 ug/ml - Z-VAD-FMK 100.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Thapsigargin_10.000_uM_DMSO_0.025_%' ~ \"Thapsigargin 10.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_nM_DMSO_0.025_%' ~ \"H2O2 100.0 nM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_100.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_DMSO_0.025_%' ~ \"H2O2 100.0 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_Disulfiram_1.000_uM' ~ \"H2O2 100.0 uM - Disulfiram 1.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_Z-VAD-FMK_100.000_uM' ~ \"H2O2 100.0 uM - Z-VAD-FMK 100.0 uM\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_2.500_uM_DMSO_0.025_%' ~ \"Disulfiram 2.5 uM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_20.000_nM_DMSO_0.025_%' ~ \"Topotecan 20.0 nM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_5.000_nM_DMSO_0.025_%' ~ \"Topotecan 5.0 nM - DMSO 0.025%\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ \"Media ctr 0.0 0\",\n", - " oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='media_ctr_0.0_0_Media_0.0_0' ~ \"Media ctr 0.0 0\"\n", + "df <- df %>%\n", + " mutate(Metadata_Treatment = case_when(\n", + " Metadata_Treatment =='DMSO_0.100_%_DMSO_0.025_%' ~ \"DMSO 0.1% - DMSO 0.025%\",\n", + " Metadata_Treatment =='DMSO_0.100_%_DMSO_1.000_%' ~ \"DMSO 0.1% - DMSO 1.0%\",\n", + " Metadata_Treatment =='DMSO_0.100_%_Z-VAD-FMK_100.000_uM' ~ \"DMSO 0.1% - Z-VAD-FMK 100.0 uM\",\n", + " Metadata_Treatment =='DMSO_0.100_%_Z-VAD-FMK_30.000_uM' ~ \"DMSO 0.1% - Z-VAD-FMK 30.0 uM\",\n", + " Metadata_Treatment =='Flagellin_1.000_ug_per_ml_DMSO_0.025_%' ~ \"Flagellin 1.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM' ~ \"Flagellin 1.0 ug/ml - Disulfiram 1.0 uM\",\n", + " Metadata_Treatment =='LPS_0.010_ug_per_ml_DMSO_0.025_%' ~ \"LPS 0.01 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_0.100_ug_per_ml_DMSO_0.025_%' ~ \"LPS 0.1 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Flagellin_0.100_ug_per_ml_DMSO_0.0_%' ~ \"Flagellin 0.1 ug/ml - DMSO 0.0%\",\n", + " Metadata_Treatment =='Flagellin_0.100_ug_per_ml_DMSO_0.025_%' ~ \"Flagellin 0.1 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Disulfiram_0.100_uM_DMSO_0.025_%' ~ \"Disulfiram 0.1 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - Disulfiram 1.0 uM\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM' ~ \"LPS 1.0 ug/ml + Nigericin 10.0 uM - Z-VAD-FMK 100.0 uM\",\n", + " Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_1.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 1.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Flagellin_1.000_ug_per_ml_DMSO_0.0_%' ~ \"Flagellin 1.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='Disulfiram_1.000_uM_DMSO_0.025_%' ~ \"Disulfiram 1.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='Thapsigargin_1.000_uM_DMSO_0.025_%' ~ \"Thapsigargin 1.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='Topotecan_10.000_nM_DMSO_0.025_%' ~ \"Topotecan 10.0 nM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 10.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_0.100_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 0.1 uM\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_1.000_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 1.0 uM\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_2.500_uM' ~ \"LPS 10.0 ug/ml - Disulfiram 2.5 uM\",\n", + " Metadata_Treatment =='LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM' ~ \"LPS 10.0 ug/ml - Z-VAD-FMK 100.0 uM\",\n", + " Metadata_Treatment =='Thapsigargin_10.000_uM_DMSO_0.025_%' ~ \"Thapsigargin 10.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='H2O2_100.000_nM_DMSO_0.025_%' ~ \"H2O2 100.0 nM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='LPS_100.000_ug_per_ml_DMSO_0.025_%' ~ \"LPS 100.0 ug/ml - DMSO 0.025%\",\n", + " Metadata_Treatment =='H2O2_100.000_uM_DMSO_0.025_%' ~ \"H2O2 100.0 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='H2O2_100.000_uM_Disulfiram_1.000_uM' ~ \"H2O2 100.0 uM - Disulfiram 1.0 uM\",\n", + " Metadata_Treatment =='H2O2_100.000_uM_Z-VAD-FMK_100.000_uM' ~ \"H2O2 100.0 uM - Z-VAD-FMK 100.0 uM\",\n", + " Metadata_Treatment =='Disulfiram_2.500_uM_DMSO_0.025_%' ~ \"Disulfiram 2.5 uM - DMSO 0.025%\",\n", + " Metadata_Treatment =='Topotecan_20.000_nM_DMSO_0.025_%' ~ \"Topotecan 20.0 nM - DMSO 0.025%\",\n", + " Metadata_Treatment =='Topotecan_5.000_nM_DMSO_0.025_%' ~ \"Topotecan 5.0 nM - DMSO 0.025%\",\n", + " Metadata_Treatment =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ \"Media ctr 0.0 0\",\n", + " Metadata_Treatment =='media_ctr_0.0_0_Media_0.0_0' ~ \"Media ctr 0.0 0\"\n", " ))\n", " # replace Media ctr 0.0 0 with Media\n", - "merged_df$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- gsub(\"Media ctr 0.0 0\", \"Media\", merged_df$oneb_Metadata_Treatment_Dose_Inhibitor_Dose)\n", + "df$Metadata_Treatment <- gsub(\"Media ctr 0.0 0\", \"Media\", df$Metadata_Treatment)\n", "\n", - "# split the oneb_Metadata_Treatment_Dose_Inhibitor_Dose into two columns by the \" - \" delimiter\n", - "merged_df <- merged_df %>%\n", - " separate(oneb_Metadata_Treatment_Dose_Inhibitor_Dose, c(\"inducer\", \"inhibitor\"), sep = \" - \", remove = FALSE)\n", + "# split the Metadata_Treatment into two columns by the \" - \" delimiter\n", + "df <- df %>%\n", + " separate(Metadata_Treatment, c(\"inducer\", \"inhibitor\"), sep = \" - \", remove = FALSE)\n", "\n", - "unique(merged_df$inducer)\n", + "unique(df$inducer)\n", "# replace the inhibitor NA with Media\n", - "merged_df$inhibitor <- ifelse(is.na(merged_df$inhibitor), \"Media\", merged_df$inhibitor)\n", - "unique(merged_df$inhibitor)\n", + "df$inhibitor <- ifelse(is.na(df$inhibitor), \"Media\", df$inhibitor)\n", + "unique(df$inhibitor)\n", "\n", "# make the group_treatment column a factor\n", - "merged_df$inducer <- factor(\n", - " merged_df$inducer,\n", + "df$inducer <- factor(\n", + " df$inducer,\n", " levels = c(\n", " 'Media',\n", " 'DMSO 0.1%',\n", @@ -1066,8 +575,8 @@ ")\n", "\n", "# make the group_treatment column a factor\n", - "merged_df$inhibitor <- factor(\n", - " merged_df$inhibitor,\n", + "df$inhibitor <- factor(\n", + " df$inhibitor,\n", " levels = c(\n", " 'Media',\n", " 'DMSO 0.025%',\n", @@ -1081,95 +590,12 @@ " 'Z-VAD-FMK 100.0 uM'\n", " )\n", ")\n", - "head(merged_df)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "vscode": { - "languageId": "r" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
A data.frame: 6 \u00d7 7
shuffledoneb_Metadata_Treatment_Dose_Inhibitor_DoseMetadata_labelsinducerinhibitormorphology_apsecretome_ap
<fct><chr><chr><fct><fct><dbl><dbl>
1Non-shuffledDMSO 0.1% - DMSO 0.025% Control DMSO 0.1% DMSO 0.025%0.70385510.2040109
2Shuffled DMSO 0.1% - DMSO 0.025% Control DMSO 0.1% DMSO 0.025%0.70283640.1997191
3Non-shuffledFlagellin 0.1 ug/ml - DMSO 0.025%PyroptosisFlagellin 0.1 ug/mlDMSO 0.025%0.93055560.7333444
4Shuffled Flagellin 0.1 ug/ml - DMSO 0.025%PyroptosisFlagellin 0.1 ug/mlDMSO 0.025%0.43430130.1481352
5Non-shuffledFlagellin 1.0 ug/ml - DMSO 0.025%PyroptosisFlagellin 1.0 ug/mlDMSO 0.025%0.85555560.7353119
6Shuffled Flagellin 1.0 ug/ml - DMSO 0.025%PyroptosisFlagellin 1.0 ug/mlDMSO 0.025%0.33735270.1340047
\n" - ], - "text/latex": [ - "A data.frame: 6 \u00d7 7\n", - "\\begin{tabular}{r|lllllll}\n", - " & shuffled & oneb\\_Metadata\\_Treatment\\_Dose\\_Inhibitor\\_Dose & Metadata\\_labels & inducer & inhibitor & morphology\\_ap & secretome\\_ap\\\\\n", - " & & & & & & & \\\\\n", - "\\hline\n", - "\t1 & Non-shuffled & DMSO 0.1\\% - DMSO 0.025\\% & Control & DMSO 0.1\\% & DMSO 0.025\\% & 0.7038551 & 0.2040109\\\\\n", - "\t2 & Shuffled & DMSO 0.1\\% - DMSO 0.025\\% & Control & DMSO 0.1\\% & DMSO 0.025\\% & 0.7028364 & 0.1997191\\\\\n", - "\t3 & Non-shuffled & Flagellin 0.1 ug/ml - DMSO 0.025\\% & Pyroptosis & Flagellin 0.1 ug/ml & DMSO 0.025\\% & 0.9305556 & 0.7333444\\\\\n", - "\t4 & Shuffled & Flagellin 0.1 ug/ml - DMSO 0.025\\% & Pyroptosis & Flagellin 0.1 ug/ml & DMSO 0.025\\% & 0.4343013 & 0.1481352\\\\\n", - "\t5 & Non-shuffled & Flagellin 1.0 ug/ml - DMSO 0.025\\% & Pyroptosis & Flagellin 1.0 ug/ml & DMSO 0.025\\% & 0.8555556 & 0.7353119\\\\\n", - "\t6 & Shuffled & Flagellin 1.0 ug/ml - DMSO 0.025\\% & Pyroptosis & Flagellin 1.0 ug/ml & DMSO 0.025\\% & 0.3373527 & 0.1340047\\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "A data.frame: 6 \u00d7 7\n", - "\n", - "| | shuffled <fct> | oneb_Metadata_Treatment_Dose_Inhibitor_Dose <chr> | Metadata_labels <chr> | inducer <fct> | inhibitor <fct> | morphology_ap <dbl> | secretome_ap <dbl> |\n", - "|---|---|---|---|---|---|---|---|\n", - "| 1 | Non-shuffled | DMSO 0.1% - DMSO 0.025% | Control | DMSO 0.1% | DMSO 0.025% | 0.7038551 | 0.2040109 |\n", - "| 2 | Shuffled | DMSO 0.1% - DMSO 0.025% | Control | DMSO 0.1% | DMSO 0.025% | 0.7028364 | 0.1997191 |\n", - "| 3 | Non-shuffled | Flagellin 0.1 ug/ml - DMSO 0.025% | Pyroptosis | Flagellin 0.1 ug/ml | DMSO 0.025% | 0.9305556 | 0.7333444 |\n", - "| 4 | Shuffled | Flagellin 0.1 ug/ml - DMSO 0.025% | Pyroptosis | Flagellin 0.1 ug/ml | DMSO 0.025% | 0.4343013 | 0.1481352 |\n", - "| 5 | Non-shuffled | Flagellin 1.0 ug/ml - DMSO 0.025% | Pyroptosis | Flagellin 1.0 ug/ml | DMSO 0.025% | 0.8555556 | 0.7353119 |\n", - "| 6 | Shuffled | Flagellin 1.0 ug/ml - DMSO 0.025% | Pyroptosis | Flagellin 1.0 ug/ml | DMSO 0.025% | 0.3373527 | 0.1340047 |\n", - "\n" - ], - "text/plain": [ - " shuffled oneb_Metadata_Treatment_Dose_Inhibitor_Dose Metadata_labels\n", - "1 Non-shuffled DMSO 0.1% - DMSO 0.025% Control \n", - "2 Shuffled DMSO 0.1% - DMSO 0.025% Control \n", - "3 Non-shuffled Flagellin 0.1 ug/ml - DMSO 0.025% Pyroptosis \n", - "4 Shuffled Flagellin 0.1 ug/ml - DMSO 0.025% Pyroptosis \n", - "5 Non-shuffled Flagellin 1.0 ug/ml - DMSO 0.025% Pyroptosis \n", - "6 Shuffled Flagellin 1.0 ug/ml - DMSO 0.025% Pyroptosis \n", - " inducer inhibitor morphology_ap secretome_ap\n", - "1 DMSO 0.1% DMSO 0.025% 0.7038551 0.2040109 \n", - "2 DMSO 0.1% DMSO 0.025% 0.7028364 0.1997191 \n", - "3 Flagellin 0.1 ug/ml DMSO 0.025% 0.9305556 0.7333444 \n", - "4 Flagellin 0.1 ug/ml DMSO 0.025% 0.4343013 0.1481352 \n", - "5 Flagellin 1.0 ug/ml DMSO 0.025% 0.8555556 0.7353119 \n", - "6 Flagellin 1.0 ug/ml DMSO 0.025% 0.3373527 0.1340047 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled\n", - "merged_df <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels + inducer + inhibitor, data=merged_df, FUN=mean)\n", - "head(merged_df)" + "head(df)" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 8, "metadata": { "vscode": { "languageId": "r" @@ -1178,7 +604,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] @@ -1186,20 +612,20 @@ "metadata": { "image/png": { "height": 900, - "width": 1020 + "width": 900 } }, "output_type": "display_data" } ], "source": [ - "width <- 17\n", + "width <- 15\n", "height <- 15\n", "options(repr.plot.width=width, repr.plot.height=height)\n", "# scatter plot with fill being the treatment dose\n", "scatter_by_treatment <- (\n", - " ggplot(merged_df, aes(x=morphology_ap, y=secretome_ap, col = inducer, shape=inhibitor))\n", - " + geom_point(size=5, alpha=1)\n", + " ggplot(df, aes(x=mAP_moprhology, y=mAP_secretome, col = inducer, shape=inhibitor))\n", + " + geom_point(size=4, alpha=0.7)\n", " + labs(x=\"Morphology mAP score\", y=\"Secretome mAP score\")\n", " + theme_bw()\n", " + ylim(0,1)\n", @@ -1263,17 +689,18 @@ " values = shapes\n", " )\n", " # make the legend 1 column\n", - " + guides(color = guide_legend(ncol = 1), shape = guide_legend(ncol = 1))\n", + " + guides(\n", + " color = guide_legend(ncol = 3), \n", + " shape = guide_legend(ncol = 1))\n", " + ggplot2::coord_fixed()\n", - " + facet_grid(.~shuffled)\n", + " + facet_grid(~shuffled)\n", + " + theme(\n", + " legend.position = \"bottom\", \n", + " legend.title.position = \"top\", \n", + " legend.title = element_text(size = 18, hjust = 0.5,face = \"bold\")\n", + " )\n", " # add y = x line\n", " + geom_abline(intercept = 0, slope = 1, linetype = \"dashed\", color = \"black\")\n", - " # move legend to bottom\n", - " + theme(legend.position = \"bottom\")\n", - " # make legend multi rows\n", - " + guides(col = guide_legend(ncol = 2), shape = guide_legend(ncol = 1))\n", - " # shift the legend to the left slightly\n", - "\n", ")\n", "scatter_by_treatment" ] @@ -1287,7 +714,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 9, "metadata": { "vscode": { "languageId": "r" @@ -1303,7 +730,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "vscode": { "languageId": "r" @@ -1331,7 +758,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "plot without title" ] diff --git a/figures/S7/scripts/S7.r b/figures/S7/scripts/S7.r index 9ee9ca364..e63398155 100644 --- a/figures/S7/scripts/S7.r +++ b/figures/S7/scripts/S7.r @@ -5,6 +5,7 @@ suppressPackageStartupMessages(suppressWarnings(library(cowplot))) suppressPackageStartupMessages(suppressWarnings(library(RColorBrewer))) suppressPackageStartupMessages(suppressWarnings(library(patchwork))) suppressPackageStartupMessages(suppressWarnings(library(tidyr))) +suppressPackageStartupMessages(suppressWarnings(library(arrow))) # load in theme source("../../utils/figure_themes.r") @@ -12,41 +13,43 @@ source("../../utils/figure_themes.r") cell_type <- "PBMC" # set path to the data morphology -# class -df_morphology_class_path <- file.path("..","..","..","9.mAP","data","processed","aggregate_mAPs","morphology","mAP_scores_class.csv") -reg_df_morphology_class_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","mAP_scores_regular_class.csv") -shuffled_morphology_class_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","mAP_scores_shuffled_feature_space_class.csv") -# treatment -treatment_df_morphology_treatment_path <- file.path("..","..","..","9.mAP","data","processed","aggregate_mAPs","morphology","mAP_scores_treatment.csv") -reg_df_morphology_treatment_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","mAP_scores_regular_treatment.csv") -shuffled_morphology_treatment_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","mAP_scores_shuffled_feature_space_treatment.csv") +morphology_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","activity_map.parquet") +shuffled_morphology_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","morphology","activity_map_shuffled.parquet") # set path to the secretome data -# class -df_secretome_class_path <- file.path("..","..","..","9.mAP","data","processed","aggregate_mAPs","secretome","mAP_scores_class.csv") -reg_df_secretome_class_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","mAP_scores_regular_class.csv") -shuffled_secretome_class_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","mAP_scores_shuffled_feature_space_class.csv") -# treatment -treatment_df_secretome_treatment_path <- file.path("..","..","..","9.mAP","data","processed","aggregate_mAPs","secretome","mAP_scores_treatment.csv") -reg_df_secretome_treatment_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","mAP_scores_regular_treatment.csv") -shuffled_secretome_treatment_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","mAP_scores_shuffled_feature_space_treatment.csv") - -# read in the data -df_morphology_class <- read.csv(df_morphology_class_path) -reg_df_morphology_class <- read.csv(reg_df_morphology_class_path) -shuffled_morphology_class <- read.csv(shuffled_morphology_class_path) - -df_morphology_treatment <- read.csv(treatment_df_morphology_treatment_path) -reg_df_morphology_treatment <- read.csv(reg_df_morphology_treatment_path) -shuffled_morphology_treatment <- read.csv(shuffled_morphology_treatment_path) - -df_secretome_class <- read.csv(df_secretome_class_path) -reg_df_secretome_class <- read.csv(reg_df_secretome_class_path) -shuffled_secretome_class <- read.csv(shuffled_secretome_class_path) - -df_secretome_treatment <- read.csv(treatment_df_secretome_treatment_path) -reg_df_secretome_treatment <- read.csv(reg_df_secretome_treatment_path) -shuffled_secretome_treatment <- read.csv(shuffled_secretome_treatment_path) + +secretome_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","activity_map.parquet") +shuffled_secretome_path <- file.path("..","..","..","9.mAP","data","processed","mAP_scores","secretome","activity_map_shuffled.parquet") + +df_morphology <- arrow::read_parquet(morphology_path) %>% + dplyr::mutate(shuffled = "Non-shuffled") %>% + dplyr::mutate(data_type = "Morphology") %>% + # rename the mean_average_precision column to specifcy morphology + # drop unnecessary columns + dplyr::select(-c("Metadata_reference_index", "indices", "p_value", "corrected_p_value", "below_p", "below_corrected_p","-log10(p-value)")) + +df_shuffled_morphology <- arrow::read_parquet(shuffled_morphology_path) %>% + dplyr::mutate(shuffled = "Shuffled") %>% + dplyr::mutate(data_type = "Morphology") %>% + # rename the mean_average_precision column to specifcy morphology + dplyr::select(-c("Metadata_reference_index", "indices", "p_value", "corrected_p_value", "below_p", "below_corrected_p","-log10(p-value)")) + + +df_secretome <- arrow::read_parquet(secretome_path) %>% + dplyr::mutate(shuffled = "Non-shuffled") %>% + dplyr::mutate(data_type = "Secretome") %>% + # rename the mean_average_precision column to specifcy secretome + dplyr::select(-c("Metadata_reference_index", "indices", "p_value", "corrected_p_value", "below_p", "below_corrected_p","-log10(p-value)")) + + +df_shuffled_secretome <- arrow::read_parquet(shuffled_secretome_path) %>% + dplyr::mutate(shuffled = "Shuffled") %>% + dplyr::mutate(data_type = "Secretome") %>% + # rename the mean_average_precision column to specifcy secretome + dplyr::select(-c("Metadata_reference_index", "indices", "p_value", "corrected_p_value", "below_p", "below_corrected_p","-log10(p-value)")) + +df <- dplyr::bind_rows(df_morphology, df_shuffled_morphology, df_secretome, df_shuffled_secretome) +head(df) levels_list <- c( 'Media', @@ -96,263 +99,80 @@ levels_list <- c( 'Topotecan_20.000_nM_DMSO_0.025_%' ) -# declare the shuffled column as a factor -# replace the values in the shuffled column -# declare the shuffled column as a factor -# replace the values in the shuffled column -df_morphology_class$shuffled <- gsub("shuffled", "Shuffled", df_morphology_class$shuffled) -df_morphology_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", df_morphology_class$shuffled) -df_morphology_class$shuffled <- factor(df_morphology_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) -df_morphology_class$Metadata_labels <- factor(df_morphology_class$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) - -df_secretome_class$shuffled <- gsub("shuffled", "Shuffled", df_secretome_class$shuffled) -df_secretome_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", df_secretome_class$shuffled) -df_secretome_class$shuffled <- factor(df_secretome_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) -df_secretome_class$Metadata_labels <- factor(df_secretome_class$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) - -df_morphology_treatment$shuffled <- gsub("shuffled", "Shuffled", df_morphology_treatment$shuffled) -df_morphology_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", df_morphology_treatment$shuffled) -df_morphology_treatment$shuffled <- factor(df_morphology_treatment$shuffled, levels = c( "Non-shuffled", "Shuffled")) -df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - -df_secretome_treatment$shuffled <- gsub("shuffled", "Shuffled", df_secretome_treatment$shuffled) -df_secretome_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", df_secretome_treatment$shuffled) -df_secretome_treatment$shuffled <- factor(df_secretome_treatment$shuffled, levels = c("Non-shuffled", "Shuffled")) -df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - - -# combine the dataframes -all_df_morphology_class <- rbind(reg_df_morphology_class, shuffled_morphology_class) -all_df_morphology_treatment <- rbind(reg_df_morphology_treatment, shuffled_morphology_treatment) -all_df_secretome_class <- rbind(reg_df_secretome_class, shuffled_secretome_class) -all_df_secretome_treatment <- rbind(reg_df_secretome_treatment, shuffled_secretome_treatment) - -all_df_morphology_class$shuffled <- gsub("shuffled", "Shuffled", all_df_morphology_class$shuffled) -all_df_morphology_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_morphology_class$shuffled) -all_df_morphology_class$shuffled <- factor(all_df_morphology_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_morphology_class$Metadata_labels <- factor(all_df_morphology_class$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) - -all_df_secretome_class$shuffled <- gsub("shuffled", "Shuffled", all_df_secretome_class$shuffled) -all_df_secretome_class$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_secretome_class$shuffled) -all_df_secretome_class$shuffled <- factor(all_df_secretome_class$shuffled, levels = c( "Non-shuffled", "Shuffled")) - -all_df_morphology_treatment$shuffled <- gsub("shuffled", "Shuffled", all_df_morphology_treatment$shuffled) -all_df_morphology_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_morphology_treatment$shuffled) -all_df_morphology_treatment$shuffled <- factor(all_df_morphology_treatment$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_morphology_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - -all_df_secretome_treatment$shuffled <- gsub("shuffled", "Shuffled", all_df_secretome_treatment$shuffled) -all_df_secretome_treatment$shuffled <- gsub("non-Shuffled", "Non-shuffled", all_df_secretome_treatment$shuffled) -all_df_secretome_treatment$shuffled <- factor(all_df_secretome_treatment$shuffled, levels = c( "Non-shuffled", "Shuffled")) -all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- factor(all_df_secretome_treatment$oneb_Metadata_Treatment_Dose_Inhibitor_Dose, levels = levels_list) - -# cobine the dfs -# get the average precision, shuffled, and Metadata_labels columns by name -subset_morphology_class <- all_df_morphology_class[,c("average_precision", "shuffled", "Metadata_labels")] -# rename the average_precision column to moprhology_ap -colnames(subset_morphology_class)[colnames(subset_morphology_class)=="average_precision"] <- "morphology_ap" - -# get the average precision, shuffled, and Metadata_labels columns by name -subset_secretome_class <- all_df_secretome_class[,c("average_precision", "shuffled", "Metadata_labels")] -# rename the average_precision column to secretome_ap -colnames(subset_secretome_class)[colnames(subset_secretome_class)=="average_precision"] <- "secretome_ap" - -# merge the dataframes -merged_df <- merge(subset_morphology_class, subset_secretome_class, by=c("shuffled", "Metadata_labels")) -head(merged_df) - - -# aggregate the data by shuffled and Metadata_labels -merged_agg <- aggregate(. ~ shuffled + Metadata_labels, data=merged_df, FUN=mean) -# combine the shuffled and Metadata_labels columns -merged_agg$group <- paste(merged_agg$shuffled, merged_agg$Metadata_labels, sep="_") -# change the text in the group column -merged_agg$group <- gsub("Non-shuffled Control", "Non-shuffled\nControl", merged_agg$group) -merged_agg$group <- gsub("Shuffled Control", "Shuffled\nControl", merged_agg$group) -merged_agg$group <- gsub("Non-shuffled_Apoptosis", "Non-shuffled\nApoptosis", merged_agg$group) -merged_agg$group <- gsub("Shuffled Apoptosis", "Shuffled\nApoptosis", merged_agg$group) -merged_agg$group <- gsub("Non-shuffled Pyroptosis", "Non-shuffled\nPyroptosis", merged_agg$group) -merged_agg$group <- gsub("Shuffled Pyroptosis", "Shuffled\nPyroptosis", merged_agg$group) -# make the group column a factor -merged_agg$group <- factor( - merged_agg$group, - levels = c( - "Non-shuffled\nControl", - "Shuffled features\nControl", - "Shuffled phenotypes\nControl", - - "Non-shuffled\nApoptosis", - "Shuffled features\nApoptosis", - "Shuffled phenotypes\nApoptosis", - - "Non-shuffled\nPyroptosis", - "Shuffled features\nPyroptosis", - "Shuffled phenotypes\nPyroptosis")) - -merged_agg - -width <- 8 -height <- 6 -options(repr.plot.width=width, repr.plot.height=height) -# plot the data -scatter_compare <- ( - ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled)) - + geom_point(size=3, alpha=1) - + labs(x="Morphology mAP score", y="Secretome mAP score") - + theme_bw() - + ggtitle("Comparison of mAP scores") - + ylim(0,1) - + xlim(0,1) - # Change the legend title - # change the legend shape - + scale_shape_manual( - name="Shuffle type", - labels=c( - "Non-shuffled", - "Shuffled features", - "Shuffled phenotypes" - ), - values=c(19, 17, 15) - ) - + scale_color_manual( - name="Class", - labels=c( - "Control", - "Apoptosis", - "Pyroptosis" - ), - values=c( - brewer.pal(3, "Dark2")[2], - brewer.pal(3, "Dark2")[1], - brewer.pal(3, "Dark2")[3] - ) -) - + figure_theme - # add y = x line - + geom_abline(intercept = 0, slope = 1, linetype="dashed") - -) -scatter_compare - -# cobine the dfs -# get the average precision, shuffled, and Metadata_labels columns by name -subset_morphology_treatment <- all_df_morphology_treatment[,c("average_precision", "shuffled", "Metadata_labels","oneb_Metadata_Treatment_Dose_Inhibitor_Dose")] -# rename the average_precision column to moprhology_ap -colnames(subset_morphology_treatment)[colnames(subset_morphology_treatment)=="average_precision"] <- "morphology_ap" - -# get the average precision, shuffled, and Metadata_labels columns by name -subset_secretome_treatment <- all_df_secretome_treatment[,c("average_precision", "shuffled", "Metadata_labels","oneb_Metadata_Treatment_Dose_Inhibitor_Dose")] -# rename the average_precision column to secretome_ap -colnames(subset_secretome_treatment)[colnames(subset_secretome_treatment)=="average_precision"] <- "secretome_ap" - -# merge the dataframes -merged_df <- merge(subset_morphology_treatment, subset_secretome_treatment, by=c("shuffled", "Metadata_labels", "oneb_Metadata_Treatment_Dose_Inhibitor_Dose")) -head(merged_df) - -# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled -merged_agg <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels, data=merged_df, FUN=mean) -# scatter plot -scatter_compare_treatment <- ( - ggplot(merged_agg, aes(x=morphology_ap, y=secretome_ap, col = Metadata_labels, shape=shuffled)) - + geom_point(size=3, alpha=0.5) - + labs(x="Morphology mAP score", y="Secretome mAP score") - + theme_bw() - + ggtitle("Comparison of mAP scores") - + ylim(0,1) - + xlim(0,1) - # Change the legend title - # change the legend shape - + scale_shape_manual( - name="Shuffle type", - labels=c( - "Non-shuffled", - "Shuffled features", - "Shuffled phenotypes" - ), - values=c(19, 17, 15) - ) - + scale_color_manual( - name="Class", - labels=c( - "Control", - "Apoptosis", - "Pyroptosis" - ), - values=c( - brewer.pal(3, "Dark2")[2], - brewer.pal(3, "Dark2")[1], - brewer.pal(3, "Dark2")[3] - ) -) - + figure_theme - # add y = x line - + geom_abline(intercept = 0, slope = 1, linetype="dashed", color = "black") - # fix coordiantes - + ggplot2::coord_fixed() - -) -scatter_compare_treatment - -head(merged_agg) - -merged_df <- merged_df %>% - mutate(oneb_Metadata_Treatment_Dose_Inhibitor_Dose = case_when( - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_DMSO_0.025_%' ~ "DMSO 0.1% - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_DMSO_1.000_%' ~ "DMSO 0.1% - DMSO 1.0%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_Z-VAD-FMK_100.000_uM' ~ "DMSO 0.1% - Z-VAD-FMK 100.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='DMSO_0.100_%_Z-VAD-FMK_30.000_uM' ~ "DMSO 0.1% - Z-VAD-FMK 30.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_DMSO_0.025_%' ~ "Flagellin 1.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM' ~ "Flagellin 1.0 ug/ml - Disulfiram 1.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_0.010_ug_per_ml_DMSO_0.025_%' ~ "LPS 0.01 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_0.100_ug_per_ml_DMSO_0.025_%' ~ "LPS 0.1 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_0.100_ug_per_ml_DMSO_0.0_%' ~ "Flagellin 0.1 ug/ml - DMSO 0.0%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_0.100_ug_per_ml_DMSO_0.025_%' ~ "Flagellin 0.1 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_0.100_uM_DMSO_0.025_%' ~ "Disulfiram 0.1 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - Disulfiram 1.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - Z-VAD-FMK 100.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_1.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 1.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Flagellin_1.000_ug_per_ml_DMSO_0.0_%' ~ "Flagellin 1.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_1.000_uM_DMSO_0.025_%' ~ "Disulfiram 1.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Thapsigargin_1.000_uM_DMSO_0.025_%' ~ "Thapsigargin 1.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_10.000_nM_DMSO_0.025_%' ~ "Topotecan 10.0 nM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 10.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_0.100_uM' ~ "LPS 10.0 ug/ml - Disulfiram 0.1 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_1.000_uM' ~ "LPS 10.0 ug/ml - Disulfiram 1.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Disulfiram_2.500_uM' ~ "LPS 10.0 ug/ml - Disulfiram 2.5 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM' ~ "LPS 10.0 ug/ml - Z-VAD-FMK 100.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Thapsigargin_10.000_uM_DMSO_0.025_%' ~ "Thapsigargin 10.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_nM_DMSO_0.025_%' ~ "H2O2 100.0 nM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='LPS_100.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 100.0 ug/ml - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_DMSO_0.025_%' ~ "H2O2 100.0 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_Disulfiram_1.000_uM' ~ "H2O2 100.0 uM - Disulfiram 1.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='H2O2_100.000_uM_Z-VAD-FMK_100.000_uM' ~ "H2O2 100.0 uM - Z-VAD-FMK 100.0 uM", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Disulfiram_2.500_uM_DMSO_0.025_%' ~ "Disulfiram 2.5 uM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_20.000_nM_DMSO_0.025_%' ~ "Topotecan 20.0 nM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='Topotecan_5.000_nM_DMSO_0.025_%' ~ "Topotecan 5.0 nM - DMSO 0.025%", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ "Media ctr 0.0 0", - oneb_Metadata_Treatment_Dose_Inhibitor_Dose =='media_ctr_0.0_0_Media_0.0_0' ~ "Media ctr 0.0 0" +# split out the morphology and secretome data +morphology_data <- df %>% dplyr::filter(data_type == "Morphology") +secretome_data <- df %>% dplyr::filter(data_type == "Secretome") +# rename the mean_average_precision column to specifcy morphology +morphology_data <- morphology_data %>% dplyr::rename(mAP_moprhology = mean_average_precision) +secretome_data <- secretome_data %>% dplyr::rename(mAP_secretome = mean_average_precision) +# drop the data_type column +morphology_data <- morphology_data %>% dplyr::select(-data_type) +secretome_data <- secretome_data %>% dplyr::select(-data_type) +# merge the data together to plot +df <- merge(morphology_data, secretome_data,by = c("Metadata_Treatment", "Metadata_labels", "shuffled")) + + +df$Metadata_labels <- factor(df$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis")) +df$Metadata_Treatment <- factor(df$Metadata_Treatment, levels =levels_list) + +df <- df %>% + mutate(Metadata_Treatment = case_when( + Metadata_Treatment =='DMSO_0.100_%_DMSO_0.025_%' ~ "DMSO 0.1% - DMSO 0.025%", + Metadata_Treatment =='DMSO_0.100_%_DMSO_1.000_%' ~ "DMSO 0.1% - DMSO 1.0%", + Metadata_Treatment =='DMSO_0.100_%_Z-VAD-FMK_100.000_uM' ~ "DMSO 0.1% - Z-VAD-FMK 100.0 uM", + Metadata_Treatment =='DMSO_0.100_%_Z-VAD-FMK_30.000_uM' ~ "DMSO 0.1% - Z-VAD-FMK 30.0 uM", + Metadata_Treatment =='Flagellin_1.000_ug_per_ml_DMSO_0.025_%' ~ "Flagellin 1.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Flagellin_1.000_ug_per_ml_Disulfiram_1.000_uM' ~ "Flagellin 1.0 ug/ml - Disulfiram 1.0 uM", + Metadata_Treatment =='LPS_0.010_ug_per_ml_DMSO_0.025_%' ~ "LPS 0.01 ug/ml - DMSO 0.025%", + Metadata_Treatment =='LPS_0.100_ug_per_ml_DMSO_0.025_%' ~ "LPS 0.1 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Flagellin_0.100_ug_per_ml_DMSO_0.0_%' ~ "Flagellin 0.1 ug/ml - DMSO 0.0%", + Metadata_Treatment =='Flagellin_0.100_ug_per_ml_DMSO_0.025_%' ~ "Flagellin 0.1 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Disulfiram_0.100_uM_DMSO_0.025_%' ~ "Disulfiram 0.1 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Disulfiram_1.000_uM' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - Disulfiram 1.0 uM", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_10.000_uM_Z-VAD-FMK_100.000_uM' ~ "LPS 1.0 ug/ml + Nigericin 10.0 uM - Z-VAD-FMK 100.0 uM", + Metadata_Treatment =='LPS_Nigericin_1.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ "LPS 1.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_1.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 1.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Flagellin_1.000_ug_per_ml_DMSO_0.0_%' ~ "Flagellin 1.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='Disulfiram_1.000_uM_DMSO_0.025_%' ~ "Disulfiram 1.0 uM - DMSO 0.025%", + Metadata_Treatment =='Thapsigargin_1.000_uM_DMSO_0.025_%' ~ "Thapsigargin 1.0 uM - DMSO 0.025%", + Metadata_Treatment =='Topotecan_10.000_nM_DMSO_0.025_%' ~ "Topotecan 10.0 nM - DMSO 0.025%", + Metadata_Treatment =='LPS_10.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 10.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_0.100_uM' ~ "LPS 10.0 ug/ml - Disulfiram 0.1 uM", + Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_1.000_uM' ~ "LPS 10.0 ug/ml - Disulfiram 1.0 uM", + Metadata_Treatment =='LPS_10.000_ug_per_ml_Disulfiram_2.500_uM' ~ "LPS 10.0 ug/ml - Disulfiram 2.5 uM", + Metadata_Treatment =='LPS_10.000_ug_per_ml_Z-VAD-FMK_100.000_uM' ~ "LPS 10.0 ug/ml - Z-VAD-FMK 100.0 uM", + Metadata_Treatment =='Thapsigargin_10.000_uM_DMSO_0.025_%' ~ "Thapsigargin 10.0 uM - DMSO 0.025%", + Metadata_Treatment =='H2O2_100.000_nM_DMSO_0.025_%' ~ "H2O2 100.0 nM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_1.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 1.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_10.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 10.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_Nigericin_100.000_ug_per_ml_3.000_uM_DMSO_0.025_%' ~ "LPS 100.0 ug/ml + Nigericin 3.0 uM - DMSO 0.025%", + Metadata_Treatment =='LPS_100.000_ug_per_ml_DMSO_0.025_%' ~ "LPS 100.0 ug/ml - DMSO 0.025%", + Metadata_Treatment =='H2O2_100.000_uM_DMSO_0.025_%' ~ "H2O2 100.0 uM - DMSO 0.025%", + Metadata_Treatment =='H2O2_100.000_uM_Disulfiram_1.000_uM' ~ "H2O2 100.0 uM - Disulfiram 1.0 uM", + Metadata_Treatment =='H2O2_100.000_uM_Z-VAD-FMK_100.000_uM' ~ "H2O2 100.0 uM - Z-VAD-FMK 100.0 uM", + Metadata_Treatment =='Disulfiram_2.500_uM_DMSO_0.025_%' ~ "Disulfiram 2.5 uM - DMSO 0.025%", + Metadata_Treatment =='Topotecan_20.000_nM_DMSO_0.025_%' ~ "Topotecan 20.0 nM - DMSO 0.025%", + Metadata_Treatment =='Topotecan_5.000_nM_DMSO_0.025_%' ~ "Topotecan 5.0 nM - DMSO 0.025%", + Metadata_Treatment =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ "Media ctr 0.0 0", + Metadata_Treatment =='media_ctr_0.0_0_Media_0.0_0' ~ "Media ctr 0.0 0" )) # replace Media ctr 0.0 0 with Media -merged_df$oneb_Metadata_Treatment_Dose_Inhibitor_Dose <- gsub("Media ctr 0.0 0", "Media", merged_df$oneb_Metadata_Treatment_Dose_Inhibitor_Dose) +df$Metadata_Treatment <- gsub("Media ctr 0.0 0", "Media", df$Metadata_Treatment) -# split the oneb_Metadata_Treatment_Dose_Inhibitor_Dose into two columns by the " - " delimiter -merged_df <- merged_df %>% - separate(oneb_Metadata_Treatment_Dose_Inhibitor_Dose, c("inducer", "inhibitor"), sep = " - ", remove = FALSE) +# split the Metadata_Treatment into two columns by the " - " delimiter +df <- df %>% + separate(Metadata_Treatment, c("inducer", "inhibitor"), sep = " - ", remove = FALSE) -unique(merged_df$inducer) +unique(df$inducer) # replace the inhibitor NA with Media -merged_df$inhibitor <- ifelse(is.na(merged_df$inhibitor), "Media", merged_df$inhibitor) -unique(merged_df$inhibitor) +df$inhibitor <- ifelse(is.na(df$inhibitor), "Media", df$inhibitor) +unique(df$inhibitor) # make the group_treatment column a factor -merged_df$inducer <- factor( - merged_df$inducer, +df$inducer <- factor( + df$inducer, levels = c( 'Media', 'DMSO 0.1%', @@ -391,8 +211,8 @@ merged_df$inducer <- factor( ) # make the group_treatment column a factor -merged_df$inhibitor <- factor( - merged_df$inhibitor, +df$inhibitor <- factor( + df$inhibitor, levels = c( 'Media', 'DMSO 0.025%', @@ -406,19 +226,15 @@ merged_df$inhibitor <- factor( 'Z-VAD-FMK 100.0 uM' ) ) -head(merged_df) - -# aggregate the data by shuffled and oneb_Metadata_Treatment_Dose_Inhibitor_Dose and shuffled -merged_df <- aggregate(. ~ shuffled + oneb_Metadata_Treatment_Dose_Inhibitor_Dose + Metadata_labels + inducer + inhibitor, data=merged_df, FUN=mean) -head(merged_df) +head(df) -width <- 17 +width <- 15 height <- 15 options(repr.plot.width=width, repr.plot.height=height) # scatter plot with fill being the treatment dose scatter_by_treatment <- ( - ggplot(merged_df, aes(x=morphology_ap, y=secretome_ap, col = inducer, shape=inhibitor)) - + geom_point(size=5, alpha=1) + ggplot(df, aes(x=mAP_moprhology, y=mAP_secretome, col = inducer, shape=inhibitor)) + + geom_point(size=4, alpha=0.7) + labs(x="Morphology mAP score", y="Secretome mAP score") + theme_bw() + ylim(0,1) @@ -482,17 +298,18 @@ scatter_by_treatment <- ( values = shapes ) # make the legend 1 column - + guides(color = guide_legend(ncol = 1), shape = guide_legend(ncol = 1)) + + guides( + color = guide_legend(ncol = 3), + shape = guide_legend(ncol = 1)) + ggplot2::coord_fixed() - + facet_grid(.~shuffled) + + facet_grid(~shuffled) + + theme( + legend.position = "bottom", + legend.title.position = "top", + legend.title = element_text(size = 18, hjust = 0.5,face = "bold") + ) # add y = x line + geom_abline(intercept = 0, slope = 1, linetype = "dashed", color = "black") - # move legend to bottom - + theme(legend.position = "bottom") - # make legend multi rows - + guides(col = guide_legend(ncol = 2), shape = guide_legend(ncol = 1)) - # shift the legend to the left slightly - ) scatter_by_treatment diff --git a/map_env.yaml b/map_env.yaml index 956ce19e7..5fa08a961 100644 --- a/map_env.yaml +++ b/map_env.yaml @@ -11,8 +11,9 @@ dependencies: - pyarrow - seaborn - matplotlib + - pytoml - pip: - - git+https://github.com/cytomining/copairs.git@v0.3.3 + - git+https://github.com/cytomining/copairs.git@v0.5.0 - kaleido - pycytominer - plotly diff --git a/output.png b/output.png deleted file mode 100644 index ca0cc191d..000000000 Binary files a/output.png and /dev/null differ