scripts generating axis coloured subcols bp for PS

scripts/plotting/subcols_axis_PS.R

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+getwd()
+setwd('~/git/LSHTM_analysis/scripts/plotting')
+getwd()
+
+#########################################################
+# TASK:
+
+#########################################################
+
+########################################################################
+# 		Installing and loading required packages and functions		   #	
+########################################################################
+
+#source('Header_TT.R')
+#source('barplot_colour_function.R')
+
+########################################################################
+#		 Read file: call script for combining df for PS			   	   #
+########################################################################
+#?????????????
+#
+########################################################
+#%% variable assignment: input and output paths & filenames
+drug = 'pyrazinamide'
+gene = 'pncA'
+gene_match = paste0(gene,'_p.')
+cat(gene_match)
+
+#=============
+# directories
+#=============
+datadir = paste0('~/git/Data')
+indir = paste0(datadir, '/', drug, '/input')
+outdir = paste0('~/git/Data', '/', drug, '/output')
+
+#======
+# input
+#======
+#in_filename = 'mcsm_complex1_normalised.csv'
+in_filename_params = paste0(tolower(gene), '_all_params.csv') 
+infile_params = paste0(outdir, '/', in_filename_params)
+cat(paste0('Input file:', infile_params) )
+
+#=======
+# output
+#=======
+
+
+#%%===============================================================
+###########################
+# Read file: struct params
+###########################
+cat('Reading struct params including mcsm:', in_filename_params)
+
+my_df = read.csv(infile_params
+                 #, stringsAsFactors = F
+                 , header = T)
+
+cat('Input dimensions:', dim(my_df)) 
+
+# clear variables
+rm(in_filename_params, infile_params)
+
+# quick checks
+colnames(my_df)
+str(my_df)
+
+# check for duplicate mutations
+if ( length(unique(my_df$mutationinformation)) != length(my_df$mutationinformation)){
+  cat(paste0('CAUTION:', ' Duplicate mutations identified'
+             , '\nExtracting these...'))
+  dup_muts = my_df[duplicated(my_df$mutationinformation),]
+  dup_muts_nu = length(unique(dup_muts$mutationinformation))
+  cat(paste0('\nDim of duplicate mutation df:', nrow(dup_muts)
+             , '\nNo. of unique duplicate mutations:', dup_muts_nu
+             , '\n\nExtracting df with unique mutations only'))
+  my_df_u = my_df[!duplicated(my_df$mutationinformation),]
+}else{
+  cat(paste0('No duplicate mutations detected'))
+  my_df_u = my_df
+}
+
+#upos = unique(my_df_u$position)
+cat('Dim of clean df:'); cat(dim(my_df_u))
+cat('\nNo. of unique mutational positions:'); cat(length(unique(my_df_u$position)))
+#======================================================
+# create a new df with unique position numbers and cols
+position = unique(my_df$position) #130
+position_cols = as.data.frame(position)
+
+head(position_cols) ; tail(position_cols)
+
+# specify active site residues and bg colour
+position = c(49, 51, 57, 71
+             , 8, 96, 138
+             , 13, 68
+             , 103, 137
+             , 133, 134) #13
+
+lab_bg = rep(c("purple" 
+               , "yellow"
+               , "cornflowerblue"
+               , "blue"
+               , "green"), times = c(4, 3, 2, 2, 2)
+)
+
+# second bg colour for active site residues
+#lab_bg2 = rep(c("white" 
+#                , "green" , "white", "green"
+#                , "white"
+#                , "white"
+#                , "white"), times = c(4
+#                                      , 1, 1, 1
+#                                      , 2
+#                                      , 2
+#                                      , 2)
+#)
+
+#%%%%%%%%%
+# revised: leave the second box coloured as the first one incase there is no second colour
+#%%%%%%%%%
+lab_bg2 = rep(c("purple" 
+                , "green", "yellow", "green"
+                , "cornflowerblue"
+                , "blue"
+                , "green"), times = c(4
+                                      , 1, 1, 1
+                                      , 2
+                                      , 2
+                                      , 2))
+
+# fg colour for labels for active site residues
+lab_fg = rep(c("white" 
+               , "black"
+               , "black"
+               , "white"
+               , "black"), times = c(4, 3, 2, 2, 2))
+
+#%%%%%%%%%
+# revised: make the purple ones black
+# fg colour for labels for active site residues
+#%%%%%%%%%
+#lab_fg = rep(c("black" 
+#               , "black"
+#               , "black"
+#               , "white"
+#               , "black"), times = c(4, 3, 2, 2, 2))               
+               
+# combined df with active sites, bg and fg colours
+aa_cols_ref = data.frame(position
+                         , lab_bg
+                         , lab_bg2
+                         , lab_fg
+                         , stringsAsFactors = F) #13, 4
+
+str(position_cols); class(position_cols)
+str(aa_cols_ref); class(aa_cols_ref)
+
+# since position is int and numeric in the two dfs resp, 
+# converting numeric to int for consistency
+aa_cols_ref$position = as.integer(aa_cols_ref$position)
+class(aa_cols_ref$position)
+
+#===========
+# Merge 1: merging positions df (position_cols) and
+# active site cols (aa_cols_ref)
+# linking column: "position"
+# This is so you can have colours defined for all positions
+#===========
+head(position_cols$position); head(aa_cols_ref$position)
+
+mut_pos_cols = merge(position_cols, aa_cols_ref
+            , by = "position"
+            , all.x = TRUE) 
+
+head(mut_pos_cols)
+# replace NA's 
+# :column "lab_bg" with "white"
+# : column "lab_fg" with "black"
+mut_pos_cols$lab_bg[is.na(mut_pos_cols$lab_bg)] <- "white"
+mut_pos_cols$lab_bg2[is.na(mut_pos_cols$lab_bg2)] <- "white"
+mut_pos_cols$lab_fg[is.na(mut_pos_cols$lab_fg)] <- "black"
+head(mut_pos_cols)
+
+#===========
+# Merge 2: Merge mut_pos_cols with mcsm df
+# Now combined the positions with aa colours with 
+# the mcsm_data
+#===========
+# dfs to merge
+df0 = my_df # my_df_o
+df1 = mut_pos_cols
+
+# check the column on which merge will be performed
+head(df0$position); tail(df0$position)
+head(df1$position); tail(df1$position)
+
+# should now have 3 extra columns
+my_df = merge(df0, df1
+              , by = "position"
+              , all.x = TRUE)
+
+# sanity check
+my_df[my_df$position == "49",]
+my_df[my_df$position == "13",]
+
+rm(df0, df1)
+#===========
+# Merge 3: Merge mut_pos_cols with mcsm df_u
+# Now combined the positions with aa colours with 
+# the mcsm_data
+#===========
+# dfs to merge
+df0 = my_df_u # my_df_u
+df1 = mut_pos_cols
+
+# check the column on which merge will be performed
+head(df0$position); tail(df0$position)
+head(df1$position); tail(df1$position)
+
+# should now have 3 extra columns
+my_df_u = merge(df0, df1
+              , by = "position"
+              , all.x = TRUE)
+
+# sanity check
+my_df[my_df$position == "49",]
+my_df[my_df$position == "13",]
+
+# clear variables
+rm(aa_cols_ref
+   , df0
+   , df1
+   , position_cols
+   , lab_bg
+   , lab_bg2
+   , lab_fg
+   , position
+   , dup_muts)
+