python

codescripts/library_concordance.py

 dat = pd.read_table(input_dat)
 
 # output files
-sample_size = dat.shape[1]-2
+sample_size = dat.shape[1]-4
 inter_number = pd.DataFrame(index=range(sample_size),columns=range(sample_size))
 union_number = pd.DataFrame(index=range(sample_size),columns=range(sample_size))
 
 for i in range(sample_size):
-    oneSNV_GT = dat.iloc[:,0].astype(str) + '_' + dat.iloc[:,1].astype(str) + '_' + dat.iloc[:,i+2].astype(str)
+    oneSNV_GT = dat.iloc[:,0].astype(str) + '_' + dat.iloc[:,1].astype(str) + '_' + dat.iloc[:,i+4].astype(str)
     print(i+1)
     for j in range(sample_size):
-        anotherSNV_GT = dat.iloc[:,0].astype(str) + '_' + dat.iloc[:,1].astype(str) + '_' + dat.iloc[:,j+2].astype(str)
+        anotherSNV_GT = dat.iloc[:,0].astype(str) + '_' + dat.iloc[:,1].astype(str) + '_' + dat.iloc[:,j+4].astype(str)
         #remove './.' and '0/0'
         oneSNV_GT = [e for e in oneSNV_GT if './.' not in e]
         oneSNV_GT = [e for e in oneSNV_GT if '0/0' not in e]
         inter_number.iloc[i,j] = len(inter)
         union_number.iloc[i,j] = len(union)
 
-inter_number.columns = dat.columns[2:dat.shape[1]]
-inter_number.index = dat.columns[2:dat.shape[1]]
-union_number.columns = dat.columns[2:dat.shape[1]]
-union_number.index = dat.columns[2:dat.shape[1]]
+inter_number.columns = dat.columns[4:dat.shape[1]]
+inter_number.index = dat.columns[4:dat.shape[1]]
+union_number.columns = dat.columns[4:dat.shape[1]]
+union_number.index = dat.columns[4:dat.shape[1]]
 
 inter_number.to_csv(output_inter_name,sep='\t')
 union_number.to_csv(output_union_name,sep='\t')

tasks/Jaccard_Index.wdl

 	output {
 		File genotype = "${chromo}.gt"
 		File snv = "${chromo}.gt.snv.txt"
-		File indel = "${chromo}.indel.txt"
+		File indel = "${chromo}.gt.indel.txt"
 		File snv_inter = "${chromo}.snv.inter.txt"
 		File snv_union = "${chromo}.snv.union.txt"
 		File indel_inter = "${chromo}.indel.inter.txt"