renamed 2 to _v2

scripts/functions/plotting_data.R

@@ -5,6 +5,17 @@
 # load libraries and functions
 library(data.table)
 library(dplyr)
+
+# ADDED: New
+geneL_normal  = c("pnca")
+geneL_na      = c("gid", "rpob")
+geneL_ppi2    = c("alr", "embb", "katg", "rpob")
+
+if (tolower(gene)%in%geneL_na){
+  
+  infilename_nca = paste0("/home/tanu/git/Misc/mcsm_na_dist/"
+                        , tolower(gene), "_nca_distances.csv")
+}
 #========================================================
 # plotting_data(): formatting data for plots
 # input args: 
@@ -20,6 +31,7 @@ library(dplyr)
 #lig_dist_cutoff  =  10 or global var LigDist_cutoff
 
 plotting_data <- function(df
+                          , gene # ADDED
                           , lig_dist_colname 
                           , lig_dist_cutoff) {
 my_df       = data.frame()
@@ -57,7 +69,28 @@ if ( length(unique(df$mutationinformation)) != length(df$mutationinformation)){
 upos = unique(my_df_u$position)
 cat("\nDim of clean df:"); cat(dim(my_df_u), "\n")
 cat("\nNo. of unique mutational positions:"); cat(length(upos), "\n")
+#===============================================
+# ADD : na distance column for genes with nucleic acid affinity
+#===============================================
+#gid_na_distcol
+if (tolower(gene)%in%geneL_na){
+
+  distcol_nca_name = read.csv(infilename_nca, header = F)
+  head(distcol_nca_name)
+  colnames(distcol_nca_name) <- c("mutationinformation", "nca_distance")
+  head(distcol_nca_name)
+  class(distcol_nca_name)
+
+  mcol = colnames(distcol_nca_name)[colnames(distcol_nca_name)%in%colnames(my_df_u)]
+  mcol
+  head(my_df_u$mutationinformation)
+  head(distcol_nca_name$mutationinformation)
   
+  my_df_u = merge(my_df_u, distcol_nca_name, 
+                     by = "mutationinformation",
+                     all = T)
+
+} 
 #===============================================
 # extract mutations <10 Angstroms and symbol
 #===============================================