sorted subcols_axis script to generate correct axis cols for both PS and lig plots

This commit is contained in:
Tanushree Tunstall 2020-08-26 16:39:10 +01:00
parent 2e53c8007a
commit e0f14ed266
9 changed files with 117 additions and 81 deletions

147
scripts/plotting/subcols_axis_PS.R Normal file → Executable file
View file

@ -1,7 +1,6 @@
#########################################################
# TASK: Adding colours to positions labels according to
# active site residues. This is so these can be seen promptly
# when visualising the barplot.
# TASK: Adding colours to dfs so they can be used for plotting
# add cols to each of the my_df* dfs
#########################################################
#=======================================================================
getwd()
@ -15,46 +14,45 @@ source("plotting_data.R")
# my_df_u_lig
# dup_muts
cat(paste0("Directories imported:"
, "\ndatadir:", datadir
, "\nindir:", indir
, "\noutdir:", outdir
, "\nplotdir:", plotdir))
cat(paste0("Variables imported:"
, "\ndrug:", drug
, "\ngene:", gene
, "\ngene_match:", gene_match
, "\nLength of upos:", length(upos)
, "\nAngstrom symbol:", angstroms_symbol))
# clear excess variable
rm(upos, dup_muts, my_df_u, my_df_u_lig)
# This is because we want to assign the colours to my_df
# and then resubset accordingly for our plots to avoid multiple merges
#=======================================================================
###########################
# Read file: struct params
###########################
cat("Reading struct params including mcsm:", in_filename_params)
# df to use: my_df
# NOTE: my_df contains duplicate muts but its ok as you are only adding
# colours to positions
my_df = read.csv(infile_params
#, stringsAsFactors = F
, header = T)
# sanity checks: ensure my_df is ordered by position: it should be
my_df$position; my_df$mutationinformation
cat("Input dimensions:", dim(my_df))
my_df_o = my_df[order(my_df$position),]
my_df_o$position; my_df_o$mutationinformation
# clear variables
rm(in_filename_params, infile_params)
head(my_df_o$position) == head(my_df$position)
head(my_df_o$mutationinformation) == head(my_df$mutationinformation)
tail(my_df_o$position) == tail(my_df$position)
tail(my_df_o$mutationinformation) == tail(my_df$mutationinformation)
# quick checks
colnames(my_df)
str(my_df)
my_df = my_df_o
# check for duplicate mutations
if ( length(unique(my_df$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$position)
cat("Dim of clean df:"); cat(dim(my_df_u))
cat("\nNo. of unique mutational positions:"); cat(length(upos))
#=======================================================================
# create a new df with unique position numbers and cols
position = unique(my_df$position) #130
position = unique(my_df$position)
position_cols = as.data.frame(position)
head(position_cols) ; tail(position_cols)
@ -143,6 +141,7 @@ mut_pos_cols = merge(position_cols, aa_cols_ref
, all.x = TRUE)
head(mut_pos_cols)
# replace NA"s
# :column "lab_bg" with "white"
# : column "lab_fg" with "black"
@ -165,39 +164,69 @@ head(df0$position); tail(df0$position)
head(df1$position); tail(df1$position)
# should now have 3 extra columns
my_df = merge(df0, df1
my_df_cols = merge(df0, df1
, by = "position"
, all.x = TRUE)
# sanity check
my_df[my_df$position == "49",]
my_df[my_df$position == "13",]
my_df_cols[my_df_cols$position == "49",]
my_df_cols[my_df_cols$position == "13",]
rm(df0, df1)
#===========
# Merge 3: Merge mut_pos_cols with mcsm df_u
# Now combined the positions with aa colours with
# the mcsm_data
#===========
# dfs to merge
df0 = my_df_u # my_df_u
df1 = mut_pos_cols
###########################
# extract unique mutation entries
###########################
# check the column on which merge will be performed
head(df0$position); tail(df0$position)
head(df1$position); tail(df1$position)
# check for duplicate mutations
if ( length(unique(my_df_cols$mutationinformation)) != length(my_df_cols$mutationinformation)){
cat(paste0("\nCAUTION:", " Duplicate mutations identified"
, "\nExtracting these..."))
dup_muts_cols = my_df_cols[duplicated(my_df_cols$mutationinformation),]
dup_muts_cols_nu = length(unique(dup_muts_cols$mutationinformation))
cat(paste0("\nDim of duplicate mutation df:", nrow(dup_muts_cols)
, "\nNo. of unique duplicate mutations:", dup_muts_cols_nu
, "\n\nExtracting df with unique mutations only"))
my_df_u_cols = my_df_cols[!duplicated(my_df_cols$mutationinformation),]
}else{
cat(paste0("\nNo duplicate mutations detected"))
my_df_u_cols = my_df_cols
}
upos = unique(my_df_u_cols$position)
cat("\nDim of clean df:"); cat(dim(my_df_u_cols))
cat("\nNo. of unique mutational positions:"); cat(length(upos), "\n")
# should now have 3 extra columns
my_df_u = merge(df0, df1
, by = "position"
, all.x = TRUE)
# sanity check
my_df[my_df$position == "49",]
my_df[my_df$position == "13",]
my_df_u_cols[my_df_u_cols$position == "49",]
my_df_u_cols[my_df_u_cols$position == "13",]
my_df_u_cols[my_df_u_cols$position == "103",]
###########################
# extract mutations <10Angstroms
###########################
table(my_df_u_cols$ligand_distance<10)
my_df_u_cols_lig = my_df_u_cols[my_df_u_cols$ligand_distance <10,]
angstroms_symbol = "\u212b"
cat(paste0("There are ", nrow(my_df_u_cols_lig), " sites lying within 10", angstroms_symbol, " of the ligand"))
#=================
# very important!
#=================
#my_axis_colours = mut_pos_cols$lab_fg # doesn't work if positions numbers are subsetted as in ligand
# need the equivalent of the mut_pos_cols for ligand
# get position numbers for ligand
lig_pos = my_df_u_cols_lig$position
# subset mut_pos_cols for ligand positions
mut_pos_cols_lig = mut_pos_cols[mut_pos_cols$position %in% lig_pos,]
#my_axis_colours = mut_pos_cols_lig$lab_fg
#====================================================================
# clear variables
rm(aa_cols_ref
, my_df
, df0
, df1
, position_cols
@ -206,3 +235,7 @@ rm(aa_cols_ref
, lab_fg
, position)
#######################################################################
# end of script
#######################################################################