#!/usr/bin/env Rscript ######################################################### # TASK: producing barplots # basic barplots with count of mutations # basic barplots with frequency of count of mutations # Depends on ## plotting_globals.R (previously dir.R) ## plotting_data.R ######################################################### # working dir getwd() setwd("~/git/LSHTM_analysis/scripts/plotting") getwd() # load libraries #source("Header_TT.R") library(ggplot2) library(data.table) library(dplyr) require("getopt", quietly = TRUE) # cmd parse arguments # load functions source("plotting_globals.R") source("plotting_data.R") ######################################################### # command line args spec = matrix(c( "drug" , "d", 1, "character", "gene" , "g", 1, "character" ), byrow = TRUE, ncol = 4) opt = getopt(spec) #FIXME: detect if script running from cmd, then set these drug = opt$drug gene = opt$gene # hardcoding when not using cmd #drug = "streptomycin" #gene = "gid" if(is.null(drug)|is.null(gene)) { stop("Missing arguments: --drug and --gene must both be specified (case-sensitive)") } ######################################################### # call functions with relevant args drug = "streptomycin" gene = "gid" import_dirs(drug, gene) if (!exists("infile") && exists("gene")){ #in_filename_params = paste0(tolower(gene), "_all_params.csv") in_filename_params = paste0(tolower(gene), "_comb_stab_struc_params.csv") # part combined for gid infile = paste0(outdir, "/", in_filename_params) } #infile = "/home/tanu/git/Data/streptomycin/output/gid_comb_stab_struc_params.csv" #infile = "" # Get the DFs out of plotting_data() pd_df = plotting_data(infile) my_df = pd_df[[1]] my_df_u = pd_df[[2]] my_df_u_lig = pd_df[[3]] dup_muts = pd_df[[4]] ######################################################### # This script: should return the following dfs, directories and variables # my_df # my_df_u # 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(my_df, upos, dup_muts, my_df_u_lig) #======================================================================= #======= # output #======= # plot 1 basic_bp_duet = paste0(tolower(gene), "_basic_barplot_PS.svg") plot_basic_bp_duet = paste0(plotdir,"/", basic_bp_duet) # plot 2 pos_count_duet = paste0(tolower(gene), "_position_count_PS.svg") plot_pos_count_duet = paste0(plotdir, "/", pos_count_duet) #======================================================================= #================ # Data for plots #================ # REASSIGNMENT as necessary df = my_df_u # sanity checks str(df) #======================================================================= #**************** # Plot 1:Count of stabilising and destabilsing muts #**************** svg(plot_basic_bp_duet) print(paste0("plot1 filename:", basic_bp_duet)) my_ats = 25 # axis text size my_als = 22 # axis label size theme_set(theme_grey()) #-------------- # start plot 1 #-------------- g = ggplot(df, aes(x = duet_outcome)) OutPlot_count = g + geom_bar(aes(fill = duet_outcome) , show.legend = TRUE) + geom_label(stat = "count" , aes(label = ..count..) , color = "black" , show.legend = FALSE , size = 10) + theme(axis.text.x = element_blank() , axis.title.x = element_blank() , axis.title.y = element_text(size=my_als) , axis.text.y = element_text(size = my_ats) , legend.position = c(0.73,0.8) , legend.text = element_text(size=my_als-2) , legend.title = element_text(size=my_als) , plot.title = element_blank()) + labs(title = "" , y = "Number of nsSNPs" #, fill="DUET Outcome" ) + scale_fill_discrete(name = "DUET Outcome" , labels = c("Destabilising", "Stabilising")) print(OutPlot_count) dev.off() table(df$duet_outcome) #======================================================================= #**************** # Plot 2: frequency of positions #**************** df_ncols = ncol(df) df_nrows = nrow(df) cat(paste0("original df dimensions:" , "\nNo. of rows:", df_nrows , "\nNo. of cols:", df_ncols , "\nNow adding column: frequency of mutational positions")) #setDT(df)[, .(pos_count := .N), by = .(position)] setDT(df)[, pos_count := .N, by = .(position)] rm(df_nrows, df_ncols) df_nrows = nrow(df) df_ncols = ncol(df) cat(paste0("revised df dimensions:" , "\nNo. of rows:", df_nrows , "\nNo. of cols:", df_ncols)) # this is cummulative table(df$pos_count) # use group by on this snpsBYpos_df <- df %>% group_by(position) %>% summarize(snpsBYpos = mean(pos_count)) table(snpsBYpos_df$snpsBYpos) #!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! # FIXME, get this mutation_info, perhaps useful! foo = select(df, mutationinformation , wild_pos , wild_type , mutant_type #, mutation_info # comes from meta data, notused yet , position , pos_count) #write.csv(foo, "/pos_count_freq.csv") #!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! #-------------- # start plot 2 #-------------- svg(plot_pos_count_duet) print(paste0("plot filename:", plot_pos_count_duet)) my_ats = 25 # axis text size my_als = 22 # axis label size # to make x axis display all positions # not sure if to use with sort or directly my_x = sort(unique(snpsBYpos_df$snpsBYpos)) g = ggplot(snpsBYpos_df, aes(x = snpsBYpos)) OutPlot_pos_count = g + geom_bar(aes (alpha = 0.5) , show.legend = FALSE) + scale_x_continuous(breaks = unique(snpsBYpos_df$snpsBYpos)) + #scale_x_continuous(breaks = my_x) + geom_label(stat = "count", aes(label = ..count..) , color = "black" , size = 10) + theme(axis.text.x = element_text(size = my_ats , angle = 0) , axis.text.y = element_text(size = my_ats , angle = 0 , hjust = 1) , axis.title.x = element_text(size = my_als) , axis.title.y = element_text(size = my_als) , plot.title = element_blank()) + labs(x = "Number of nsSNPs" , y = "Number of Sites") print(OutPlot_pos_count) dev.off() ######################################################################## # end of PS barplots ########################################################################