made logo_plot.R source script that pull in all the data
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2 changed files with 43 additions and 193 deletions
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@ -1,28 +1,9 @@
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#!/usr/bin/env Rscript
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#########################################################
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# TASK: producing logoplot
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# from data and/or from sequence
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#########################################################
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# working dir and loading libraries
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getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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source("Header_TT.R")
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source("../functions/plotting_globals.R")
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source("../functions/plotting_data.R")
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source("../functions/combining_dfs_plotting.R")
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###########################################################
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# command line args
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#********************
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#drug = 'streptomycin'
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#gene = 'gid'
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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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@ -32,158 +13,41 @@ spec = matrix(c(
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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_params = opt$data_file1
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infile_metadata = opt$data_file2
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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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# input
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# Input
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#===========
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#---------------------
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# call: import_dirs()
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#---------------------
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import_dirs(drug, gene)
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#---------------------------
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# call: plotting_data()
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#---------------------------
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#if (!exists("infile_params") && exists("gene")){
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if (!is.character(infile_params) && exists("gene")){ # when running as cmd
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#in_filename_params = paste0(tolower(gene), "_all_params.csv")
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in_filename_params = paste0(tolower(gene), "_comb_afor.csv") # part combined for gid
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infile_params = paste0(outdir, "/", in_filename_params)
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cat("\nInput file for mcsm comb data not specified, assuming filename: ", infile_params, "\n")
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}
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# Input 1: read <gene>_comb_afor.csv
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cat("\nReading mcsm combined data file: ", infile_params)
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mcsm_df = read.csv(infile_params, header = T)
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pd_df = plotting_data(mcsm_df)
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my_df_u = pd_df[[2]] # this forms one of the input for combining_dfs_plotting()
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#--------------------------------
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# call: combining_dfs_plotting()
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#--------------------------------
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#if (!exists("infile_metadata") && exists("gene")){
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if (!is.character(infile_metadata) && exists("gene")){ # when running as cmd
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in_filename_metadata = paste0(tolower(gene), "_metadata.csv") # part combined for gid
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infile_metadata = paste0(outdir, "/", in_filename_metadata)
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cat("\nInput file for gene metadata not specified, assuming filename: ", infile_metadata, "\n")
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}
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# Input 2: read <gene>_meta data.csv
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cat("\nReading meta data file: ", infile_metadata)
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gene_metadata <- read.csv(infile_metadata
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, stringsAsFactors = F
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, header = T)
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all_plot_dfs = combining_dfs_plotting(my_df_u
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, gene_metadata
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, lig_dist_colname = 'ligand_distance'
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, lig_dist_cutoff = 10)
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merged_df3 = all_plot_dfs[[2]]
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source("get_plotting_dfs.R")
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#===========
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# output
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#===========
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logo_plot = "logo_plot.svg"
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plot_logo_plot = paste0(plotdir,"/", logo_plot)
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logo_or_plotname = "logo_or_plot.svg"
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plot_logo_or = paste0(plotdir,"/", logo_or_plotname)
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######################################################################
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# Data for plots
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# you need merged_df2 or merged_df2_comp
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# since this is one-many relationship
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# i.e the same SNP can belong to multiple lineages
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# using the _comp dataset means
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# we lose some muts and at this level, we should use
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# as much info as available, hence use df with NA
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logo_logOR_plotname = "logo_logOR_plot.svg"
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plot_logo_logOR = paste0(plotdir,"/", logo_logOR_plotname)
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# This will the first plotting df
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# Then subset this to extract dr muts only (second plottig df)
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####################################################################
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##############################################################################
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#%%%%%%%%%%%%%%%%%%%%%%%%%
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# uncomment as necessary
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# REASSIGNMENT
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#my_data = merged_df2
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#my_data = merged_df2_comp
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my_data = merged_df3
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#my_data = merged_df3_comp
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#%%%%%%%%%%%%%%%%%%%%%%%%%%
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#================================
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# Logo plot: custom height (OR)
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#================================
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cat("Logo plot with OR as y axis:", plot_logo_or)
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svg(plot_logo_or, width = 30 , height = 6)
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# quick checks
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colnames(my_data)
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str(my_data)
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c1 = unique(my_data$position)
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nrow(my_data)
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cat("No. of rows in my_data:", nrow(my_data)
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, "\nDistinct positions corresponding to snps:", length(c1)
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, "\n===========================================================")
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#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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# FIXME: Think and decide what you want to remove
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# mut_pos_occurence < 1 or sample_pos_occurrence <1
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# get freq count of positions so you can subset freq<1
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#require(data.table)
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#setDT(my_data)[, mut_pos_occurrence := .N, by = .(position)] #265, 14
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#extract freq_pos>1
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#my_data_snp = my_data[my_data$occurrence!=1,]
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#u = unique(my_data_snp$position) #73
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#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# REASSIGNMENT to prevent changing code
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my_data_snp = my_data
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#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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#=======================================================================
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#%% logo plots from dataframe
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#############
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# PLOTS: ggseqlogo with custom height
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# https://omarwagih.github.io/ggseqlogo/
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#############
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foo = my_data_snp[, c("position"
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, "mutant_type","duet_scaled", "or_mychisq"
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, "mut_prop_polarity", "mut_prop_water")]
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my_data_snp$log10or = log10(my_data_snp$or_mychisq)
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logo_data = my_data_snp[, c("position"
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, "mutant_type", "or_mychisq", "log10or")]
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logo_data_or = my_data_snp[, c("position", "mutant_type", "or_mychisq")]
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wide_df_or <- logo_data_or %>% spread(position, or_mychisq, fill = 0.0)
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wide_df_or = as.matrix(wide_df_or)
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rownames(wide_df_or) = wide_df_or[,1]
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dim(wide_df_or)
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wide_df_or = wide_df_or[,-1]
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str(wide_df_or)
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position_or = as.numeric(colnames(wide_df_or))
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#===========================================
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#custom height (OR) logo plot: CORRECT x-axis labelling
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#============================================
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# custom height (OR) logo plot: yayy works
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cat("Logo plot with OR as y axis:", plot_logo_plot)
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svg(plot_logo_plot, width = 30 , height = 6)
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logo_or = ggseqlogo(wide_df_or, method="custom", seq_type="aa") + ylab("my custom height") +
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logo_or = ggseqlogo(wide_df_or
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, method = "custom"
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, seq_type = "aa") + ylab("my custom height") +
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theme( axis.text.x = element_text(size = 12
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, angle = 90
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, hjust = 1
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print(logo_or)
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dev.off()
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#%% end of logo plot with OR as height
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#=======================================================================
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# extracting data with log10R
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logo_data_logor = my_data_snp[, c("position", "mutant_type", "log10or")]
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wide_df_logor <- logo_data_logor %>% spread(position, log10or, fill = 0.0)
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#=======================================
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# Logo plot: custom height (Log10 OR)
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#=======================================
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cat("Logo plot with log10 OR as y axis:", plot_logo_logOR)
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svg(plot_logo_logOR, width = 30 , height = 6)
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wide_df_logor = as.matrix(wide_df_logor)
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rownames(wide_df_logor) = wide_df_logor[,1]
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wide_df_logor = subset(wide_df_logor, select = -c(1) )
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colnames(wide_df_logor)
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wide_df_logor_m = data.matrix(wide_df_logor)
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rownames(wide_df_logor_m)
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colnames(wide_df_logor_m)
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# FIXME
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#my_ylim_up = as.numeric(max(wide_df_logor_m)) * 5
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#my_ylim_low = as.numeric(min(wide_df_logor_m))
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position_logor = as.numeric(colnames(wide_df_logor_m))
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# custom height (log10OR) logo plot: yayy works
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ggseqlogo(wide_df_logor_m, method="custom", seq_type="aa") + ylab("my custom height") +
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ggseqlogo(wide_df_logor_m
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, method = "custom"
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, seq_type="aa") + ylab("my custom height") +
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theme(legend.position = "bottom"
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, axis.text.x = element_text(size = 11
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, axis.text.x = element_text(size = 13
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, angle = 90
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, hjust = 1
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, vjust = 0.4)
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, axis.text.y = element_text(size = 15
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, axis.text.y = element_text(size = 20
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, angle = 0
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, hjust = 1
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, vjust = 0))+
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, vjust = 0)
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, axis.title.y = element_text(size = 25)
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, axis.title.x = element_text(size = 20))+
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scale_x_discrete("Position"
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#, breaks
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, labels = position_logor
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, limits = factor(1:length(position_logor)))+
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ylab("Log (Odds Ratio)") +
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scale_y_continuous(limits = c(0, 9))
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#=======================================================================
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#%% end of script
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#=======================================================================
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dev.off()
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######################################################################=
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# End of script
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######################################################################=
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@ -41,9 +41,7 @@ sources:
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-fb flag has default if not supplied
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#========================
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# ./logo_multiple_muts.R : FIXME,
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Error in grid.Call(L_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : polygon edge not found (new)
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https://stackoverflow.com/questions/34220883/error-in-grid-calll-textbounds-as-graphicsannotxlabel-xx-xy-polygon
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# ./logo_multiple_muts.R
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#========================
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./logo_multiple_muts.R -d streptomycin -g gid
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## 1 svg of multiple muts for all positions > 1 muts (mutations + wt)
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note:
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-fa flag has default if not supplied
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-fb flag has default if not supplied
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- fa flag has default if not supplied
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- fb flag has default if not supplied
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- Error in grid.Call fixed by commenting out image rendering on console
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#========================
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# ./logo_combined.R : FIXME,
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Error in grid.Call(L_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : polygon edge not found (new)
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https://stackoverflow.com/questions/34220883/error-in-grid-calll-textbounds-as-graphicsannotxlabel-xx-xy-polygon
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# ./logo_combined.R
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#========================
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sources:
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'logo_plots.R' + 'logo_multiple_muts.R'
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note:
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-fa flag has default if not supplied
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-fb flag has default if not supplied
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- fa flag has default if not supplied
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- fb flag has default if not supplied
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- Error in grid.Call fixed by commenting out image rendering on console
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########################################################################
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# TODO
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