258 lines
No EOL
7.5 KiB
R
Executable file
258 lines
No EOL
7.5 KiB
R
Executable file
#!/usr/bin/env Rscript
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#########################################################
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# TASK: producing barplots
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# basic barplots with count of mutations
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# basic barplots with frequency of count of mutations
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# Depends on
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## plotting_globals.R (previously dir.R)
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## plotting_data.R
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#########################################################
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# working dir
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getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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# load libraries
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#source("Header_TT.R")
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library(ggplot2)
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library(data.table)
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library(dplyr)
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require("getopt", quietly = TRUE) # cmd parse arguments
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# load functions
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source("plotting_globals.R")
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source("plotting_data.R")
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#########################################################
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# command line args
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#********************
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# !!!FUTURE TODO!!!
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# Can pass additional params of output/plot dir by user.
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# Not strictly required for my workflow since it is optimised
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# to have a streamlined input/output flow without filename worries.
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#********************
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spec = matrix(c(
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"drug" ,"d", 1, "character",
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"gene" ,"g", 1, "character",
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"data" ,"f", 2, "character"
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), byrow = TRUE, ncol = 4)
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opt = getopt(spec)
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#FIXME: detect if script running from cmd, then set these
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drug = opt$drug
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gene = opt$gene
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infile = opt$data
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# hardcoding when not using cmd
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#drug = "streptomycin"
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#gene = "gid"
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if(is.null(drug)|is.null(gene)) {
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stop("Missing arguments: --drug and --gene must both be specified (case-sensitive)")
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}
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#########################################################
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# call functions with relevant args
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#------------------------------------------
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# import_dirs()
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# should return the follwoing variables:
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# datadir
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# indir
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# outdir
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# plotdir
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# dr_muts_col
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# other_muts_col
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# resistance_col
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#--------------------------------------------
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import_dirs(drug, gene)
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#---------------------------------------------
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# plotting_data()
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# should return the following dfs:
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# my_df
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# my_df_u
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# my_df_u_lig
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# dup_muts
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#----------------------------------------------
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#infile = "/home/tanu/git/Data/streptomycin/output/gid_comb_stab_struc_params.csv"
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#infile = ""
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#if (!exists("infile") && exists("gene")){
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if (!is.character(infile) && exists("gene")){
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#in_filename_params = paste0(tolower(gene), "_all_params.csv")
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in_filename_params = paste0(tolower(gene), "_comb_stab_struc_params.csv") # part combined for gid
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infile = paste0(outdir, "/", in_filename_params)
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cat("\nInput file not specified, assuming filename: ", infile, "\n")
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}
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# Get the DFs out of plotting_data()
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pd_df = plotting_data(infile)
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my_df = pd_df[[1]]
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my_df_u = pd_df[[2]]
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my_df_u_lig = pd_df[[3]]
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dup_muts = pd_df[[4]]
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#########################################################
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cat(paste0("Directories imported:"
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, "\ndatadir:", datadir
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, "\nindir:", indir
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, "\noutdir:", outdir
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, "\nplotdir:", plotdir))
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cat(paste0("Variables imported:"
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, "\ndrug:", drug
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, "\ngene:", gene))
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#, "\ngene_match:", gene_match
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#, "\nLength of upos:", length(upos)
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#, "\nAngstrom symbol:", angstroms_symbol))
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#=======================================================================
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#=======
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# output
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#=======
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# plot 1
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basic_bp_ligand = paste0(tolower(gene), "_basic_barplot_LIG.svg")
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plot_basic_bp_ligand = paste0(plotdir,"/", basic_bp_ligand)
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# plot 2
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pos_count_ligand = paste0(tolower(gene), "_position_count_LIG.svg")
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plot_pos_count_ligand = paste0(plotdir, "/", pos_count_ligand)
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#=======================================================================
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#================
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# Data for plots
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#================
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# REASSIGNMENT as necessary
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df = my_df_u_lig
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# sanity checks
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str(df)
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#=====================================================================
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#****************
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# Plot 1: Count of stabilising and destabilsing muts
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#****************
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#svg("basic_barplots_LIG.svg")
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svg(plot_basic_bp_ligand)
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print(paste0("plot1 filename:", basic_bp_ligand))
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my_ats = 25 # axis text size
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my_als = 22 # axis label size
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theme_set(theme_grey())
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#--------------
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# start plot 1
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#--------------
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g = ggplot(df, aes(x = ligand_outcome))
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OutPlot_lig_count = g + geom_bar(aes(fill = ligand_outcome)
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, show.legend = TRUE) +
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geom_label(stat = "count"
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, aes(label = ..count..)
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, color = "black"
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, show.legend = FALSE
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, size = 10) +
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theme(axis.text.x = element_blank()
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, axis.title.x = element_blank()
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, axis.title.y = element_text(size=my_als)
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, axis.text.y = element_text(size = my_ats)
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, legend.position = c(0.73,0.8)
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, legend.text = element_text(size=my_als-2)
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, legend.title = element_text(size=my_als)
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, plot.title = element_blank()) +
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labs(title = ""
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, y = "Number of nsSNPs"
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#, fill="ligand_outcome"
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) +
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scale_fill_discrete(name = "Ligand Outcome"
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, labels = c("Destabilising", "Stabilising"))
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print(OutPlot_lig_count)
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dev.off()
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table(df$ligand_outcome)
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#=======================================================================
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#****************
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# Plot 2: frequency of positions
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#****************
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df_ncols = ncol(df)
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df_nrows = nrow(df)
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cat(paste0("original df dimensions:"
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, "\nNo. of rows:", df_nrows
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, "\nNo. of cols:", df_ncols
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, "\nNow adding column: frequency of mutational positions"))
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#setDT(df)[, .(pos_count := .N), by = .(position)]
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setDT(df)[, pos_count := .N, by = .(position)]
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rm(df_nrows, df_ncols)
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df_nrows = nrow(df)
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df_ncols = ncol(df)
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cat(paste0("revised df dimensions:"
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, "\nNo. of rows:", df_nrows
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, "\nNo. of cols:", df_ncols))
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# this is cummulative
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table(df$pos_count)
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# use group by on this
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snpsBYpos_df <- df %>%
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group_by(position) %>%
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summarize(snpsBYpos = mean(pos_count))
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table(snpsBYpos_df$snpsBYpos)
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#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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# FIXME, get this mutation_info, perhaLIG useful!
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foo = select(df, mutationinformation
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, wild_pos
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, wild_type
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, mutant_type
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#, mutation_info # comes from meta data, notused yet
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, position
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, pos_count)
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#write.csv(foo, "/pos_count_freq.csv")
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#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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#--------------
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# start plot 2
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#--------------
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#svg("position_count_LIG.svg")
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svg(plot_pos_count_ligand)
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print(paste0("plot filename:", plot_pos_count_ligand))
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my_ats = 25 # axis text size
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my_als = 22 # axis label size
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# to make x axis display all positions
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# not sure if to use with sort or directly
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my_x = sort(unique(snpsBYpos_df$snpsBYpos))
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g = ggplot(snpsBYpos_df, aes(x = snpsBYpos))
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OutPlot_lig_pos_count = g + geom_bar(aes (alpha = 0.5)
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, show.legend = FALSE) +
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scale_x_continuous(breaks = unique(snpsBYpos_df$snpsBYpos)) +
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#scale_x_continuous(breaks = my_x) +
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geom_label(stat = "count", aes(label = ..count..)
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, color = "black"
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, size = 10) +
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theme(axis.text.x = element_text(size = my_ats
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, angle = 0)
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, axis.text.y = element_text(size = my_ats
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, angle = 0
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, hjust = 1)
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, axis.title.x = element_text(size = my_als)
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, axis.title.y = element_text(size = my_als)
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, plot.title = element_blank()) +
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labs(x = "Number of nsSNPs"
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, y = "Number of Sites")
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print(OutPlot_lig_pos_count)
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dev.off()
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########################################################################
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# end of LIG barplots
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######################################################################## |