fixed source to contain plotting cols and pos_count correctly

scripts/functions/combining_dfs_plotting.R

@@ -41,7 +41,7 @@ geneL_ppi2    = c("alr", "embb", "katg", "rpob")
 
 combining_dfs_plotting <- function(  my_df_u
                                    , gene_metadata
-                                   , gene # ADDED
+                                   #, gene # ADDED
                                    , lig_dist_colname = ''
                                    , lig_dist_cutoff = ''){
 
@@ -686,8 +686,11 @@ combining_dfs_plotting <- function(  my_df_u
   min( merged_df3['avg_lig_affinity_scaled']); max( merged_df3['avg_lig_affinity_scaled'])
   
   ###################################################################
-  # Rectify pos_count column in merged_df3
+  #--------------------------------------------
-  # The one in merged_df2 is correct
+  # merged_df3: Rectify pos_count column
+  # Rename existing pos_count colum to reflect
+  # that it is correct according to merged_df2
+  #--------------------------------------------
   
   nc_pc_CHANGE = which(colnames(merged_df3)== "pos_count"); nc_pc_CHANGE
   colnames(merged_df3)[nc_pc_CHANGE] = "df2_pos_count_all"
@@ -707,16 +710,25 @@ combining_dfs_plotting <- function(  my_df_u
   nc_change = which(colnames(merged_df3) == "n")
   colnames(merged_df3)[nc_change] <- "pos_count"
   class(merged_df3)
+
+  ####################################################################
+  #-------------------------------------------------
+  # merged_df2: Rename existing pos_count 
+  # column to df2_pos_count_all like in above df
+  #-------------------------------------------------
+  nc_pc_CHANGE_df2 = which(colnames(merged_df2)== "pos_count"); nc_pc_CHANGE_df2
+  colnames(merged_df2)[nc_pc_CHANGE_df2] = "df2_pos_count_all"
+  head(merged_df2$pos_count)
+  head(merged_df2$df2_pos_count_all)
+  
   ####################################################################
   # ADD: distance to Nucleic acid column for na genes
-  
+  # already done in plotting_data
-  
   ####################################################################
-  #TODO
   # Choose few columns to return as plot_df
   
-  
+  merged_df3 = merged_df3[, colnames(merged_df3)%in%c(plotting_cols, "pos_count", "df2_pos_count_all")]
-  
+  merged_df2 = merged_df2[, colnames(merged_df2)%in%c(plotting_cols, "df2_pos_count_all")]
   
   ####################################################################
   return(list(  merged_df2

scripts/functions/dm_om_data.R

@@ -121,7 +121,7 @@ dm_om_wf_lf_data <- function(df
   mmcsm_lig_dn2 = paste0("mmCSM-lig"); mmcsm_lig_dn2
   
   
-  na_dist_dn   = paste0("NA Dist(", angstroms_symbol, ")"); na_dist_dn
+  na_dist_dn   = paste0("Dist to NA (", angstroms_symbol, ")"); na_dist_dn
   mcsm_na_dn   = paste0("mCSM-NA ", stability_suffix); mcsm_na_dn
   
   ppi2_dist_dn = paste0("PPI Dist(", angstroms_symbol, ")"); ppi2_dist_dn
@@ -174,7 +174,8 @@ dm_om_wf_lf_data <- function(df
     )
     
     display_common_colnames = c(snp_colname
-                                , mut_colname            , "dst_mode"          , mut_info_label_colname
+                                , mut_colname
+                                , "dst_mode"          , mut_info_label_colname
                                 , aa_pos_colname
                                 
                                 , "duet_stability_change" , duet_dn            , "duet_outcome"

scripts/functions/plotting_data.R

@@ -7,14 +7,10 @@ library(data.table)
 library(dplyr)
 
 # ADDED: New
-geneL_normal  = c("pnca")
+# geneL_normal  = c("pnca")
-geneL_na      = c("gid", "rpob")
+# geneL_na      = c("gid", "rpob")
-geneL_ppi2    = c("alr", "embb", "katg", "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: 
@@ -31,8 +27,9 @@ if (tolower(gene)%in%geneL_na){
 
 plotting_data <- function(df
                           , gene # ADDED
-                          , lig_dist_colname 
+                          , lig_dist_colname = 'ligand_distance'
-                          , lig_dist_cutoff) {
+                          , lig_dist_cutoff = 10
+                          ) {
   my_df       = data.frame()
   my_df_u     = data.frame()
   my_df_u_lig = data.frame()
@@ -89,11 +86,15 @@ plotting_data <- function(df
   #                      all = T)
   # 
   # } 
+  geneL_na=c("gid","rpob")
 
   if (tolower(gene)%in%geneL_na){
+    infilename_nca = paste0("/home/tanu/git/Misc/mcsm_na_dist/"
+                            , tolower(gene), "_nca_distances.csv")
     distcol_nca_name = read.csv(infilename_nca, header = F)
 
     if (tolower(gene)=='rpob'){
+      
       print('WARNING: running special-case handler for rpoB')
       
       # create 5uhc equivalent column for mutationinformation

scripts/plotting/get_plotting_dfs.R

@@ -88,7 +88,7 @@ cat("\nDim of meta data file: ", dim(gene_metadata))
 
 all_plot_dfs = combining_dfs_plotting(my_df_u
                                       , gene_metadata
-                                      , gene = gene # ADDED
+                                      #, gene = gene # ADDED
                                       , lig_dist_colname = LigDist_colname
                                       , lig_dist_cutoff = LigDist_cutoff)
 

scripts/plotting/plotting_colnames.R

@@ -1,6 +1,4 @@
-geneL_normal  = c("pnca")
+# Initialise the required dfs based on gene name
-geneL_na      = c("gid", "rpob")
-geneL_ppi2    = c("alr", "embb", "katg", "rpob")
 
 # LigDist_colname # from globals used
 # ppi2Dist_colname #from globals used 
@@ -11,7 +9,7 @@ common_cols = c("mutationinformation"
                 , drug, "drug_name"
                 , "mutation", "mutation_info"
                 , "wild_type", "mutant_type", "position"
-                , "pos_count"
+                #, "pos_count", "df2_pos_count_all" 
                 , "snp_frequency"
                 , "total_id_ucount"
                 , "drtype", "drtype_mode", "drtype_max"
@@ -63,7 +61,7 @@ common_outcome_affinity_cols = c( "ligand_outcome"
 #======================================================
 # Plotting cols + affinity cols: conditional on gene
 #======================================================
-if (tolower(gene)%in%geneL_normal){
+if (tolower(gene)%in%c("pnca")){
   plotting_cols = common_cols
   
   raw_affinity_cols = common_raw_affinity_cols
@@ -73,7 +71,7 @@ if (tolower(gene)%in%geneL_normal){
   
 }
 # ppi2 genes
-if (tolower(gene)%in%geneL_ppi2){
+if (tolower(gene)%in%c("alr", "embb", "katg")){
   plotting_cols = c(common_cols,
                     ppi2Dist_colname,
                     "mcsm_ppi2_affinity", "mcsm_ppi2_scaled", "mcsm_ppi2_outcome")
@@ -87,7 +85,7 @@ if (tolower(gene)%in%geneL_ppi2){
 }
 
 #na_genes
-if (tolower(gene)%in%geneL_na){
+if (tolower(gene)%in%c("gid")){
   plotting_cols = c(common_cols,
                     naDist_colname,
                     "mcsm_na_affinity", "mcsm_na_scaled", "mcsm_na_outcome")
@@ -95,13 +93,28 @@ if (tolower(gene)%in%geneL_na){
   raw_affinity_cols      = c(common_raw_affinity_cols     , "mcsm_na_affinity")
   scaled_affinity_cols   = c(common_scaled_affinity_cols  , "mcsm_na_scaled")
   outcome_affinity_cols  = c(common_outcome_affinity_cols , "mcsm_na_outcome")
-  affinity_dist_colnames      = c(LigDist_colname, ppi2Dist_colname, naDist_colname)
+  affinity_dist_colnames = c(LigDist_colname, naDist_colname)
   
   }
 
 if (tolower(gene)%in%c("rpob")){
-  plotting_cols = c(plotting_cols, "X5uhc_position","X5uhc_offset")
+  #plotting_cols = c(plotting_cols, "X5uhc_position","X5uhc_offset")
+  plotting_cols = c(common_cols,
+                    ppi2Dist_colname,
+                    "mcsm_ppi2_affinity", "mcsm_ppi2_scaled", "mcsm_ppi2_outcome",
+                    naDist_colname,
+                    "mcsm_na_affinity", "mcsm_na_scaled", "mcsm_na_outcome", 
+                    "X5uhc_position","X5uhc_offset")
+  
+  
+  raw_affinity_cols     = c(common_raw_affinity_cols     , "mcsm_ppi2_affinity", "mcsm_na_affinity")
+  scaled_affinity_cols  = c(common_scaled_affinity_cols  , "mcsm_ppi2_scaled" , "mcsm_na_scaled")
+  outcome_affinity_cols = c(common_outcome_affinity_cols , "mcsm_ppi2_outcome", "mcsm_na_outcome")
+  outcome_affinity_cols = c(common_outcome_affinity_cols , "mcsm_na_outcome")
+  affinity_dist_colnames      = c(LigDist_colname, ppi2Dist_colname, naDist_colname)
+  
 }
+
 #=======================================
 # All: affinity cols: based on above confition
 #========================================

scripts/plotting/plotting_thesis/basic_barplots.R

@@ -57,7 +57,7 @@ merged_df3 = merged_df3[, !colnames(merged_df3)%in%c("pos_count")]
 head(merged_df3$pos_count)
 
 df3 = merged_df3[, colnames(merged_df3)%in%plotting_cols]
-#"nca_distance"%in%colnames(df3)
+"nca_distance"%in%colnames(df3)
 
 #=======
 # output