a massive waste of time

scripts/functions/dm_om_data.R

@@ -8,7 +8,7 @@
 ##################################################################
 # from plotting_globals.R
 # DistCutOff, LigDist_colname, ppi2Dist_colname, naDist_colname 
-gene
+#gene
 
 dm_om_wf_lf_data <- function(df
                              , gene              # from globals
@@ -28,9 +28,15 @@ dm_om_wf_lf_data <- function(df
   sum(is.na(df$maf2))
   
   # Initialise the required dfs based on gene name
+  #geneL_normal  = c("pnca")
+  #geneL_na      = c("gid", "rpob")
+  #geneL_ppi2    = c("alr", "embb", "katg", "rpob")
+  
+  #ADDED: IMPORTANT for rpob to be in both to make sure all data is returned
   geneL_normal  = c("pnca")
-  geneL_na      = c("gid", "rpob")
+  geneL_both    = c("rpob")
-  geneL_ppi2    = c("alr", "embb", "katg", "rpob")
+  geneL_ppi2    = c("alr", "embb", "katg")
+  geneL_na      = c("gid")
   
   # common_dfs
   common_dfsL     = list(
@@ -59,6 +65,14 @@ dm_om_wf_lf_data <- function(df
     wf_lf_dataL   = common_dfsL
   }
   
+  if (tolower(gene)%in%geneL_ppi2){
+    additional_dfL   = list(
+      wf_mcsm_ppi2   = data.frame()
+      , lf_mcsm_ppi2 = data.frame()
+    )
+    wf_lf_dataL      = c(common_dfsL, additional_dfL)
+  }
+  
   if (tolower(gene)%in%geneL_na){
     additional_dfL = list(
       wf_mcsm_na   = data.frame()
@@ -67,13 +81,16 @@ dm_om_wf_lf_data <- function(df
     wf_lf_dataL    = c(common_dfsL, additional_dfL)
   }
   
-  if (tolower(gene)%in%geneL_ppi2){
+  if (tolower(gene)%in%geneL_both){
     additional_dfL = list(
-      wf_mcsm_ppi2   = data.frame()
+      wf_mcsm_ppi2   = data.frame(),
-      , lf_mcsm_ppi2 = data.frame()
+      lf_mcsm_ppi2 = data.frame(),
+      wf_mcsm_na   = data.frame(),
+      lf_mcsm_na = data.frame()
     )
     wf_lf_dataL      = c(common_dfsL, additional_dfL)
   }
+  
   cat("\nInitializing an empty list of length:"
       , length(wf_lf_dataL))
   
@@ -237,6 +254,38 @@ dm_om_wf_lf_data <- function(df
       
     }
     
+    if (tolower(gene)%in%geneL_both){
+      colnames_to_extract = c(
+        common_colnames, 
+        "mcsm_ppi2_affinity" ,
+        "mcsm_ppi2_scaled" , 
+        "mcsm_ppi2_outcome"  , 
+        ppi2Dist_colname,
+        "mcsm_na_affinity"   , 
+        "mcsm_na_scaled"  , 
+        "mcsm_na_outcome"   , 
+        naDist_colname
+      )
+      display_colnames    = c(
+        display_common_colnames,
+        "mcsm_ppi2_affinity", 
+        mcsm_ppi2_dn, 
+        "mcsm_ppi2_outcome",
+        ppi2_dist_dn,
+        "mcsm_na_affinity",
+        mcsm_na_dn,
+        "mcsm_na_outcome",
+        na_dist_dn
+      )
+      comb_df_sl      = df[, colnames_to_extract]
+      colnames(comb_df_sl)   = display_colnames
+      comb_df_sl_ppi2 = comb_df_sl[comb_df_sl[[ppi2_dist_dn]]<DistCutOff,]
+      comb_df_sl_na   = comb_df_sl[comb_df_sl[[na_dist_dn]]<DistCutOff,]
+      static_cols_end = c(na_dist_dn, static_cols_end_common)
+      
+    }
+    
+    
     # Affinity filtered data: mcsm-lig: COMMON for all genes, mcsm-lig --> LigDist_colname
     comb_df_sl_lig = comb_df_sl[comb_df_sl[[lig_dist_dn]]<DistCutOff,]
     

scripts/functions/plotting_data.R

@@ -12,7 +12,6 @@ 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")
 }
@@ -72,25 +71,65 @@ 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){
-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)
+  # 
+  # } 
   
+  if (tolower(gene)%in%geneL_na){
     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
+      my_df_u$X5uhc_mutationinformation = paste0(my_df_u$wild_type,
+                                                 my_df_u$X5uhc_position,
+                                                 my_df_u$mutant_type)
+      
+      colnames(distcol_nca_name) <- c("X5uhc_mutationinformation", "nca_distance")
+      
+      # do stuff here
+      mcol = colnames(distcol_nca_name)[colnames(distcol_nca_name)%in%colnames(my_df_u)]
+      cat(paste0("\nMerging for gene: ", tolower(gene), "\non column: ", mcol))
+      
+      head(my_df_u$mutationinformation)
+      head(distcol_nca_name$X5uhc_mutationinformation)
+      
+      my_df_u = merge(my_df_u, distcol_nca_name, 
+                      by = "X5uhc_mutationinformation",
+                      all = T)
+      
+    } else {
       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
+      cat(paste0("\nMerging for gene: ", tolower(gene), "\non column: ", 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
   #===============================================
@@ -111,3 +150,4 @@ return(all_df)
 ########################################################################
 #               end of data extraction and cleaning for plots          #
 ########################################################################
+

scripts/plotting/get_plotting_dfs.R

@@ -60,8 +60,8 @@ pd_df = plotting_data(mcsm_df
 my_df   = pd_df[[1]] 
 my_df_u = pd_df[[2]] # this forms one of the input for combining_dfs_plotting()
 
-max_ang <- round(max(my_df_u[LigDist_colname]))
+max_ang <- round(max(my_df_u[[LigDist_colname]]))
-min_ang <- round(min(my_df_u[LigDist_colname]))
+min_ang <- round(min(my_df_u[[LigDist_colname]]))
 
 cat("\nLigand distance colname:", LigDist_colname
     , "\nThe max distance", gene, "structure df" , ":", max_ang, "\u212b"
@@ -128,6 +128,11 @@ geneL_normal  = c("pnca")
 geneL_na      = c("gid", "rpob")
 geneL_ppi2    = c("alr", "embb", "katg", "rpob")
 
+# geneL_normal  = c("pnca")
+# geneL_both    = c("rpob")
+# geneL_ppi2    = c("alr", "embb", "katg")
+# geneL_na      = c("gid")
+
 all_dm_om_df = dm_om_wf_lf_data(df = merged_df3, gene = gene)
 
 wf_duet      = all_dm_om_df[['wf_duet']]
@@ -158,15 +163,27 @@ lf_provean   = all_dm_om_df[['lf_provean']]
 wf_dist_gen   = all_dm_om_df[['wf_dist_gen']]
 lf_dist_gen   = all_dm_om_df[['lf_dist_gen']]
 
+# ppi2 genes
+if (tolower(gene)%in%geneL_ppi2){
+  wf_mcsm_ppi2 = all_dm_om_df[['wf_mcsm_ppi2']]
+  lf_mcsm_ppi2 = all_dm_om_df[['lf_mcsm_ppi2']]
+}
+
+# na genes
 if (tolower(gene)%in%geneL_na){
   wf_mcsm_na   = all_dm_om_df[['wf_mcsm_na']]
   lf_mcsm_na   = all_dm_om_df[['lf_mcsm_na']]
 }
 
-if (tolower(gene)%in%geneL_ppi2){
+# both ppi2+na genes:: NOT NEEDED Here as its is handled by the two ifs above
-  wf_mcsm_ppi2 = all_dm_om_df[['wf_mcsm_ppi2']]
+# if (tolower(gene)%in%geneL_both){
-  lf_mcsm_ppi2 = all_dm_om_df[['lf_mcsm_ppi2']]
+#   wf_mcsm_ppi2 = all_dm_om_df[['wf_mcsm_ppi2']]
-}
+#   lf_mcsm_ppi2 = all_dm_om_df[['lf_mcsm_ppi2']]
+#   
+#   wf_mcsm_na   = all_dm_om_df[['wf_mcsm_na']]
+#   lf_mcsm_na   = all_dm_om_df[['lf_mcsm_na']]
+# }
+
 
 s2 = c("\nSuccessfully sourced other_plots_data.R")
 cat(s2)