155 lines
No EOL
5.2 KiB
R
155 lines
No EOL
5.2 KiB
R
#!/usr/bin/env Rscript
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#########################################################
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# TASK: Get formatted data for plots
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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/my_pairs_panel.R") # with lower panel turned off
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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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# cmd args passed
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# in from other scripts
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# to call this
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#********************
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#drug = 'streptomycin'
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#gene = 'gid'
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#====================
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# variables for lig
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#====================
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LigDist_colname = "ligand_distance"
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LigDist_cutoff = 20
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#===========
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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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, lig_dist_colname = LigDist_colname
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, lig_dist_cutoff = LigDist_cutoff)
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my_df = pd_df[[1]]
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my_df_u = pd_df[[2]] # this forms one of the input for combining_dfs_plotting()
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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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# 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 = LigDist_colname
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, lig_dist_cutoff = LigDist_cutoff)
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merged_df2 = all_plot_dfs[[1]]
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merged_df3 = all_plot_dfs[[2]]
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merged_df2_comp = all_plot_dfs[[3]]
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merged_df3_comp = all_plot_dfs[[4]]
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merged_df2_lig = all_plot_dfs[[5]]
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merged_df3_lig = all_plot_dfs[[6]]
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merged_df2_comp_lig = all_plot_dfs[[7]]
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merged_df3_comp_lig = all_plot_dfs[[8]]
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####################################################################
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# Data for logoplots
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####################################################################
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#-------------------------
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# choose df for logoplot
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#-------------------------
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logo_data = merged_df3
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#logo_data = merged_df3_comp
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# quick checks
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colnames(logo_data)
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str(logo_data)
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c1 = unique(logo_data$position)
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nrow(logo_data)
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cat("No. of rows in my_data:", nrow(logo_data)
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, "\nDistinct positions corresponding to snps:", length(c1)
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, "\n===========================================================")
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#=======================================================================
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#%% logo plots from dataframe
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#############
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# PLOTS
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#############
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foo = logo_data[, c("position"
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, "mutant_type","duet_scaled", "or_mychisq"
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, "mut_prop_polarity", "mut_prop_water")]
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logo_data$log10or = log10(logo_data$or_mychisq)
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logo_data_plot = logo_data[, c("position"
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, "mutant_type", "or_mychisq", "log10or")]
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logo_data_plot_or = logo_data[, c("position", "mutant_type", "or_mychisq")]
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wide_df_or <- logo_data_plot_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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# logo data: logOR
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#==================
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# extracting data with log10R
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logo_data_plot_logor = logo_data[, c("position", "mutant_type", "log10or")]
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wide_df_logor <- logo_data_plot_logor %>% spread(position, log10or, fill = 0.0)
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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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position_logor = as.numeric(colnames(wide_df_logor_m))
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########################################################################
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# End of script
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######################################################################## |