minor changes

rules/clustering.smk

@@ -19,7 +19,6 @@ rule clustering_louvain:
 		genes = config["clustering"]["genes_to_vis"],
 		subclustering = config["clustering"]["subclustering"],
 		clustering_resolution = config["clustering"]["clustering_resolution"],
-		#subclustering_resolution = config["clustering"]["subclustering_resolution"]
 	script:
 		"../scripts/clustering.py"
 
@@ -41,7 +40,8 @@ rule specter:
 	
 rule clustering_specter:
         input:
-                expand("file_dir/post_vis_data_{downsampling}.h5ad", downsampling=config["downsampling"]["downsampling_method"])
+                expand("file_dir/post_vis_data_{downsampling}.h5ad", downsampling=config["downsampling"]["downsampling_method"]),
+                "file_dir/specter_clustering.csv"
         output:
                 "file_dir/post_clustering_specter.h5ad",
                 "file_dir/annotation_list_specter.npy",
@@ -60,7 +60,6 @@ rule clustering_specter:
                 genes = config["clustering"]["genes_to_vis"],
                 subclustering = config["clustering"]["subclustering"],
                 clustering_resolution = config["clustering"]["clustering_resolution"],
-                #subclustering_resolution = config["clustering"]["subclustering_resolution"]
         script:
                 "../scripts/clustering_specter.py"
 

scripts/differential_testing.R

@@ -63,17 +63,9 @@ result_ent[,FDR:=p.adjust(`Pr(>Chisq)`, 'fdr')]
 ent_de = result_ent[result_ent$FDR<as.numeric(snakemake@config[["differential_testing"]][["DE_threshold"]]),, drop=F]
 ent_de = ent_de[order(ent_de$FDR),]
 
-print("hier kommt DE_threshold")
-print(as.numeric(snakemake@config[["differential_testing"]][["DE_threshold"]]))
-#ent_all = result_ent[order(result_ent$FDR),]
-
 name_of_csv = paste("results/",name,"_diff_testing.csv", sep="")
 write.csv(ent_de, name_of_csv, row.names=FALSE)
 
-#name_of_csv2 = paste("results/",name,"_diff_testing.csv", sep="")
-#write.csv(ent_all,name_of_csv2, row.names=FALSE)
-
-print("done mit einem Durchlauf")
 }
 
 

scripts/enrichment_vis.R

 library("dplyr")
 library("ggplot2")
 
-print(snakemake@wildcards[["cluster"]])
-
 name <- snakemake@wildcards[["cluster"]]
 data <- read.csv(file = snakemake@input[[1]])
 

scripts/gene_set_analysis.py

 import pandas as pd
 from gprofiler import GProfiler
 import gprofiler
-#import matplotlib.pyplot as plt
-#import os
-print("EN_threshold")
-print(float(snakemake.params.EN_threshold))
-print(snakemake.wildcards.cluster)
 
 file = pd.read_csv("results/"+ snakemake.wildcards.cluster +"_diff_testing.csv")
 
@@ -19,16 +14,3 @@ enrich_results = enrichment.set_index('native').sort_values('p_value').iloc[:,[2
 
 enrich_results.to_csv("results/"+snakemake.wildcards.cluster+"_enrich_results.csv", sep=",")
 
-#from gprofiler_plotting import plot_enrich
-
-
-#plt.figure(1)
-#heatmap = sb.heatmap(cell_annotation_norm, cbar=False, annot=True)
-#heatmap.autoscale()
-#heatmap = heatmap.get_figure()
-#heatmap.savefig("figures/marker_genes_32_4.png")
-
-#plt.figure(1)
-#temp = plot_enrich(paneth_enrich_results)
-#temp = temp.get_figure()
-#temp.savefig("figures/paneth_enrich_graph.jpg")