Full working version of TReNCo

trenco_modules/trenco_core.py

@@ -936,19 +936,16 @@ def tis_enh_gene_net(sample, outdir, matrix1, matrix2, gene_vect, threads):
     p.join()
 
     print('Gathering all weights from all TADs')    
-    all_network = tf_pro_mx.multiply(g_vect.T, axis=1)
-    all_network.to_csv('process/{}_tf_promoter_matrix.txt'.format(sample), sep='\t')
+    tf_gene_wgt = tf_pro_mx.multiply(g_vect.T, axis=1)
+    tf_gene_wgt.to_csv('process/{}_tf_promoter_matrix.txt'.format(sample), sep='\t')
     
-    for df in dfs:
-        all_network.add(df)
+    all_network = pd.concat(dfs, sort = False, axis=1)
+    all_network.fillna(0, inplace=True)
 
-    #all_network = pd.concat(dfs, sort = False)
-    #all_network.fillna(0, inplace=True)
-
-    #all_network_add = all_network.add(tfxpro_wgt, fill_value=0)
+    all_network_add = all_network.add(tf_gene_wgt, fill_value=0)
 
     hdf = pd.HDFStore('results/networks/{}_full_network.h5'.format(sample))
-    hdf['results/network'] = all_network
+    hdf['results/network'] = all_network_add
     hdf.close()
 
     print(all_network.shape)