diff --git a/scripts/count_vars_ML.R b/scripts/count_vars_ML.R
index 8d2f4b8..28cf570 100644
--- a/scripts/count_vars_ML.R
+++ b/scripts/count_vars_ML.R
@@ -4,7 +4,7 @@
 #source("~/git/LSHTM_analysis/config/embb.R")
 #source("~/git/LSHTM_analysis/config/gid.R")
 #source("~/git/LSHTM_analysis/config/katg.R")
-source("~/git/LSHTM_analysis/config/pnca.R")
+#source("~/git/LSHTM_analysis/config/pnca.R")
 #source("~/git/LSHTM_analysis/config/rpob.R")
 
 source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
@@ -80,35 +80,35 @@ write.csv(merged_df2, outfile_merged_df2)
 ###################################################
 ###################################################
 ###################################################
-
-source("~/git/LSHTM_analysis/config/alr.R")
-source("~/git/LSHTM_analysis/config/embb.R")
-source("~/git/LSHTM_analysis/config/gid.R")
-source("~/git/LSHTM_analysis/config/katg.R")
-source("~/git/LSHTM_analysis/config/pnca.R")
-source("~/git/LSHTM_analysis/config/rpob.R")
-
-df3_filename = paste0("/home/tanu/git/Data/", drug, "/output/", tolower(gene), "_merged_df3.csv")
-df3 = read.csv(df3_filename)
-
-# mutationinformation
-length(unique((df3$mutationinformation)))
-
-#dm _om
-table(df3$mutation_info)
-table(df3$mutation_info_labels)
-table(df3$mutation_info_orig)
-table(df3$mutation_info_labels_orig)
-
-# test_set
-na_count <-sapply(df3, function(y) sum(length(which(is.na(y)))))
-na_count[drug]
-
-# training set
-table(df3[drug])
-
-# drtype: MDR and XDR
-#table(df3$drtype) orig i.e. incorrect ones!
-table(df3$drtype_mode_labels)
-
-
+# 
+# source("~/git/LSHTM_analysis/config/alr.R")
+# source("~/git/LSHTM_analysis/config/embb.R")
+# source("~/git/LSHTM_analysis/config/gid.R")
+# source("~/git/LSHTM_analysis/config/katg.R")
+# source("~/git/LSHTM_analysis/config/pnca.R")
+# source("~/git/LSHTM_analysis/config/rpob.R")
+# 
+# df3_filename = paste0("/home/tanu/git/Data/", drug, "/output/", tolower(gene), "_merged_df3.csv")
+# df3 = read.csv(df3_filename)
+# 
+# # mutationinformation
+# length(unique((df3$mutationinformation)))
+# 
+# #dm _om
+# table(df3$mutation_info)
+# table(df3$mutation_info_labels)
+# table(df3$mutation_info_orig)
+# table(df3$mutation_info_labels_orig)
+# 
+# # test_set
+# na_count <-sapply(df3, function(y) sum(length(which(is.na(y)))))
+# na_count[drug]
+# 
+# # training set
+# table(df3[drug])
+# 
+# # drtype: MDR and XDR
+# #table(df3$drtype) orig i.e. incorrect ones!
+# table(df3$drtype_mode_labels)
+# 
+#