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Mar 13, 2025
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redo map without death labels #169

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bfc98ca
redo map without death labels
MikeLippincott Mar 12, 2025
65871c7
rerun shuffled mAP
MikeLippincott Mar 13, 2025
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596 changes: 239 additions & 357 deletions 9.mAP/notebooks/0.generate_map_scores_morphology.ipynb
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520 changes: 215 additions & 305 deletions 9.mAP/notebooks/1.generate_map_scores_secretome.ipynb
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60 changes: 30 additions & 30 deletions 9.mAP/notebooks/2.visualize_map_scores.ipynb
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30 changes: 28 additions & 2 deletions 9.mAP/scripts/0.generate_map_scores_morphology.py
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Original file line number Diff line number Diff line change
Expand Up @@ -124,7 +124,7 @@
# In[8]:


pos_sameby = ["Metadata_Treatment", "Metadata_labels", reference_col]
pos_sameby = ["Metadata_Treatment", reference_col]
pos_diffby = []
neg_sameby = []
neg_diffby = ["Metadata_Treatment", reference_col]
Expand All @@ -148,7 +148,33 @@
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()
# add apoptosis, pyroptosis and healthy columns to dataframe
activity_map["Apoptosis"] = activity_map.apply(
lambda row: row["Metadata_Treatment"] in apoptosis_ground_truth,
axis=1,
)
activity_map["Pyroptosis"] = activity_map.apply(
lambda row: row["Metadata_Treatment"] in pyroptosis_ground_truth,
axis=1,
)
activity_map["Control"] = activity_map.apply(
lambda row: row["Metadata_Treatment"] in control_ground_truth,
axis=1,
)

# merge apoptosis, pyroptosis, and healthy columns into one column
activity_map["Metadata_labels"] = activity_map.apply(
lambda row: "Apoptosis"
if row["Apoptosis"]
else "Pyroptosis"
if row["Pyroptosis"]
else "Control",
axis=1,
)
metadata_labels = activity_map.pop("Metadata_labels")
activity_map.insert(1, "Metadata_labels", metadata_labels)
# # drop apoptosis, pyroptosis, and healthy columns
activity_map.drop(columns=["Apoptosis", "Pyroptosis", "Control"], inplace=True)


# In[10]:
Expand Down
28 changes: 27 additions & 1 deletion 9.mAP/scripts/1.generate_map_scores_secretome.py
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Expand Up @@ -149,7 +149,33 @@
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()
# add apoptosis, pyroptosis and healthy columns to dataframe
activity_map["Apoptosis"] = activity_map.apply(
lambda row: row["Metadata_Treatment"] in apoptosis_ground_truth,
axis=1,
)
activity_map["Pyroptosis"] = activity_map.apply(
lambda row: row["Metadata_Treatment"] in pyroptosis_ground_truth,
axis=1,
)
activity_map["Control"] = activity_map.apply(
lambda row: row["Metadata_Treatment"] in control_ground_truth,
axis=1,
)

# merge apoptosis, pyroptosis, and healthy columns into one column
activity_map["Metadata_labels"] = activity_map.apply(
lambda row: "Apoptosis"
if row["Apoptosis"]
else "Pyroptosis"
if row["Pyroptosis"]
else "Control",
axis=1,
)
metadata_labels = activity_map.pop("Metadata_labels")
activity_map.insert(1, "Metadata_labels", metadata_labels)
# # drop apoptosis, pyroptosis, and healthy columns
activity_map.drop(columns=["Apoptosis", "Pyroptosis", "Control"], inplace=True)


# In[10]:
Expand Down
2 changes: 1 addition & 1 deletion 9.mAP/scripts/2.visualize_map_scores.r
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Expand Up @@ -312,7 +312,7 @@ scatter_by_treatment <- (
'Topotecan 10.0 nM',
'Topotecan 20.0 nM'
),
values = colors)
values = colors_5)
+ scale_shape_manual(
name = "Inhibitor",
labels = c(
Expand Down
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4 changes: 2 additions & 2 deletions figures/4.figure4/notebooks/figure4.ipynb
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651 changes: 563 additions & 88 deletions figures/S7/notebooks/S7.ipynb
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29 changes: 14 additions & 15 deletions figures/S7/scripts/S7.r
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Expand Up @@ -113,8 +113,10 @@ df <- merge(morphology_data, secretome_data,by = c("Metadata_Treatment", "Metada


df$Metadata_labels <- factor(df$Metadata_labels, levels = c("Control", "Apoptosis", "Pyroptosis"))
df$Metadata_Treatment <- factor(df$Metadata_Treatment, levels =levels_list)
# df$Metadata_Treatment <- factor(df$Metadata_Treatment, levels =levels_list)

length(unique(df$Metadata_Treatment))
unique(df$Metadata_Treatment)
df <- df %>%
mutate(Metadata_Treatment = case_when(
Metadata_Treatment =='DMSO_0.100_%_DMSO_0.025_%' ~ "DMSO 0.1% - DMSO 0.025%",
Expand All @@ -125,7 +127,7 @@ df <- df %>%
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_0.0_%' ~ "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%",
Expand All @@ -134,7 +136,7 @@ df <- df %>%
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 =='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%",
Expand All @@ -155,11 +157,15 @@ df <- df %>%
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"
Metadata_Treatment =='Media' ~ "Media",
# Metadata_Treatment =='media_ctr_0.0_0_Media_ctr_0.0_0' ~ "Media",
# Metadata_Treatment =='media_ctr_0.0_0_Media_0.0_0' ~ "Media"
))
# replace Media ctr 0.0 0 with Media
df$Metadata_Treatment <- gsub("Media ctr 0.0 0", "Media", df$Metadata_Treatment)
length(unique(df$Metadata_Treatment))

unique(df$Metadata_Treatment)


# split the Metadata_Treatment into two columns by the " - " delimiter
df <- df %>%
Expand All @@ -176,34 +182,26 @@ df$inducer <- factor(
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'
Expand All @@ -227,6 +225,7 @@ df$inhibitor <- factor(
)
)
head(df)
unique(df$inducer)

width <- 15
height <- 15
Expand Down Expand Up @@ -279,7 +278,7 @@ scatter_by_treatment <- (
'Topotecan 10.0 nM',
'Topotecan 20.0 nM'
),
values = colors)
values = colors_5)
+ scale_shape_manual(
name = "Inhibitor",
labels = c(
Expand Down
33 changes: 33 additions & 0 deletions figures/utils/figure_themes.r
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Expand Up @@ -247,3 +247,36 @@ colors_4 <- c(
)


colors_5 <- c(
'Media' = colorgrad1[1],
'DMSO 0.1%' = colorgrad1[2],

'Flagellin 0.1 ug/ml'= colorgrad5[1],
'Flagellin 1.0 ug/ml' = colorgrad5[2],

'LPS 0.01 ug/ml' = colorgrad2[1],
'LPS 0.1 ug/ml' = colorgrad2[2],
'LPS 1.0 ug/ml' = colorgrad2[3],
'LPS 10.0 ug/ml' = colorgrad2[4],
'LPS 100.0 ug/ml' = colorgrad2[5],
'LPS 1.0 ug/ml + Nigericin 1.0 uM' = colorgrad2[6],
'LPS 1.0 ug/ml + Nigericin 3.0 uM' = colorgrad2[7],
'LPS 1.0 ug/ml + Nigericin 10.0 uM' = colorgrad2[8],
'LPS 100.0 ug/ml + Nigericin 1.0 uM' = colorgrad2[9],
'LPS 100.0 ug/ml + Nigericin 3.0 uM' = colorgrad2[10],
'LPS 100.0 ug/ml + Nigericin 10.0 uM' = colorgrad2[11],

'H2O2 100.0 nM' = colorgrad7[1],
'H2O2 100.0 uM' = colorgrad7[2],

'Disulfiram 0.1 uM' = colorgrad4[3],
'Disulfiram 1.0 uM' = colorgrad4[4],
'Disulfiram 2.5 uM' = colorgrad4[5],

'Thapsigargin 1.0 uM' = colorgrad8[1],
'Thapsigargin 10.0 uM' = colorgrad8[2],

'Topotecan 5.0 nM' = colorgrad9[1],
'Topotecan 10.0 nM' = colorgrad9[2],
'Topotecan 20.0 nM' = colorgrad9[3]
)