add option to export gene by spot matrix

panpipes/panpipes/pipeline_deconvolution_spatial/pipeline.yml

@@ -89,6 +89,7 @@ Cell2Location:
 
  # -------------------------------
   save_models: False # Default False; whether to save the reference and spatial mapping models
+  export_gene_by_spot: False # Default False; whether to save a gene by spot matrix for each cell type in a layer
 
 
 

panpipes/python_scripts/run_cell2location.py

@@ -49,6 +49,9 @@
 parser.add_argument("--save_models",
                     default=False,
                     help="whether to save the reference & spatial mapping models")
+parser.add_argument("--export_gene_by_spot",
+                    default=False,
+                    help="whether to save a gene by spot matrix for each cell type in a layer")
 
 
 # parameters for feature selection: 
@@ -148,6 +151,11 @@
     save_models = False
 else:
     save_models = True
+
+if (args.export_gene_by_spot is False) or (args.export_gene_by_spot == "False"): 
+    export_gene_by_spot = False
+else:
+    export_gene_by_spot = True
 
 if (args.remove_mt is True) or (args.remove_mt == "True"): 
     remove_mt = True
@@ -320,6 +328,14 @@
 L.info("Plotting QC plots")
 cell2loc_plot_QC_reconstr(model_spatial, figdir + "/QC_spatial_reconstruction_accuracy.png")
 
+# export a gene by spot matrix for each cell type
+if export_gene_by_spot:
+    # Compute expected expression per cell type
+    expected_dict = model_spatial.module.model.compute_expected_per_cell_type(model_spatial.samples["post_sample_q05"], model_spatial.adata_manager)
+    # Add to anndata layers
+    for i, n in enumerate(model_spatial.factor_names_):
+        sdata_st["table"].layers[n] = expected_dict['mu'][i]
+
 
 #plot output
 L.info("Plotting spatial embedding plot coloured by 'q05_cell_abundance_w_sf'")