added the almost done shiny for barplots subcolours
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c599d28377
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6 changed files with 267 additions and 263 deletions
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@ -12,6 +12,7 @@ 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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source("../functions/bp_subcolours.R")
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#********************
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# cmd args passed
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@ -25,7 +26,7 @@ source("../functions/combining_dfs_plotting.R")
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#====================
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LigDist_colname = "ligand_distance"
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LigDist_cutoff = 20
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LigDist_cutoff = 10
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#===========
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# input
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@ -38,8 +39,8 @@ 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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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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@ -61,8 +62,8 @@ 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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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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@ -89,6 +90,139 @@ 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 subcols barplot (~heatmpa)
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####################################################################
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# can include: mutation, or_kin, pwald, af_kin
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cols_to_select = c("mutationinformation", "drtype"
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#, "wild_type"
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, "position"
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#, "mutant_type"
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, "chain", "ligand_id", "ligand_distance"
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, "duet_stability_change", "duet_outcome", "duet_scaled"
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, "ligand_affinity_change", "ligand_outcome", "affinity_scaled"
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, "ddg", "foldx_scaled", "foldx_outcome"
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, "deepddg", "deepddg_outcome"
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, "asa", "rsa", "rd_values", "kd_values")
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#, "af", "or_mychisq", "pval_fisher"
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#, "or_fisher", "or_logistic", "pval_logistic")
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#, "wt_prop_water", "mut_prop_water", "wt_prop_polarity", "mut_prop_polarity"
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#, "wt_calcprop", "mut_calcprop")
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#=======================
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# Data for sub colours
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# barplot: PS
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#=======================
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cat("\nNo. of cols to select:", length(cols_to_select))
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subcols_df_ps = merged_df3[, cols_to_select]
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cat("\nNo of unique positions for ps:"
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, length(unique(subcols_df_ps$position)))
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# add count_pos col that counts the no. of nsSNPS at a position
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setDT(subcols_df_ps)[, pos_count := .N, by = .(position)]
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# should be a factor
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if (is.factor(subcols_df_ps$duet_outcome)){
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cat("\nDuet_outcome is factor")
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table(subcols_df_ps$duet_outcome)
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}else{
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cat("\nConverting duet_outcome to factor")
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subcols_df_ps$duet_outcome = as.factor(subcols_df_ps$duet_outcome)
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table(subcols_df_ps$duet_outcome)
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}
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# should be -1 and 1
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min(subcols_df_ps$duet_scaled)
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max(subcols_df_ps$duet_scaled)
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tapply(subcols_df_ps$duet_scaled, subcols_df_ps$duet_outcome, min)
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tapply(subcols_df_ps$duet_scaled, subcols_df_ps$duet_outcome, max)
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# check unique values in normalised data
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cat("\nNo. of unique values in duet scaled, no rounding:"
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, length(unique(subcols_df_ps$duet_scaled)))
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# No rounding
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my_grp = subcols_df_ps$duet_scaled; length(my_grp)
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# Add rounding is to be used
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n = 3
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subcols_df_ps$duet_scaledR = round(subcols_df_ps$duet_scaled, n)
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cat("\nNo. of unique values in duet scaled", n, "places rounding:"
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, length(unique(subcols_df_ps$duet_scaledR)))
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my_grp_r = subcols_df_ps$duet_scaledR # rounding
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# Add grp cols
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subcols_df_ps$group <- paste0(subcols_df_ps$duet_outcome, "_", my_grp, sep = "")
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subcols_df_ps$groupR <- paste0(subcols_df_ps$duet_outcome, "_", my_grp_r, sep = "")
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# Call the function to create the palette based on the group defined above
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subcols_ps <- ColourPalleteMulti(subcols_df_ps, "duet_outcome", "my_grp")
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subcolsR_ps <- ColourPalleteMulti(subcols_df_ps, "duet_outcome", "my_grp_r")
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print(paste0("Colour palette generated for my_grp: ", length(subcols_ps), " colours"))
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print(paste0("Colour palette generated for my_grp_r: ", length(subcolsR_ps), " colours"))
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#=======================
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# Data for sub colours
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# barplot: LIG
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#=======================
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cat("\nNo. of cols to select:", length(cols_to_select))
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subcols_df_lig = merged_df3_lig[, cols_to_select]
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cat("\nNo of unique positions for LIG:"
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, length(unique(subcols_df_lig$position)))
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# should be a factor
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if (is.factor(subcols_df_lig$ligand_outcome)){
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cat("\nLigand_outcome is factor")
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table(subcols_df_lig$ligand_outcome)
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}else{
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cat("\nConverting ligand_outcome to factor")
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subcols_df_lig$ligand_outcome = as.factor(subcols_df_lig$ligand_outcome)
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table(subcols_df_lig$ligand_outcome)
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}
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# should be -1 and 1
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min(subcols_df_lig$affinity_scaled)
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max(subcols_df_lig$affinity_scaled)
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tapply(subcols_df_lig$affinity_scaled, subcols_df_lig$ligand_outcome, min)
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tapply(subcols_df_lig$affinity_scaled, subcols_df_lig$ligand_outcome, max)
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# check unique values in normalised data
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cat("\nNo. of unique values in affinity scaled, no rounding:"
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, length(unique(subcols_df_lig$affinity_scaled)))
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# No rounding
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my_grp_lig = subcols_df_lig$affinity_scaled; length(my_grp_lig)
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# Add rounding is to be used
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n = 3
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subcols_df_lig$affinity_scaledR = round(subcols_df_lig$affinity_scaled, n)
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cat("\nNo. of unique values in duet scaled", n, "places rounding:"
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, length(unique(subcols_df_lig$affinity_scaledR)))
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my_grp_lig_r = subcols_df_lig$affinity_scaledR # rounding
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# Add grp cols
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subcols_df_lig$group_lig <- paste0(subcols_df_lig$ligand_outcome, "_", my_grp_lig, sep = "")
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subcols_df_lig$group_ligR <- paste0(subcols_df_lig$ligand_outcome, "_", my_grp_lig_r, sep = "")
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# Call the function to create the palette based on the group defined above
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subcols_lig <- ColourPalleteMulti(subcols_df_lig, "ligand_outcome", "my_grp_lig")
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subcolsR_lig <- ColourPalleteMulti(subcols_df_lig, "ligand_outcome", "my_grp_lig_r")
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print(paste0("Colour palette generated for my_grp: ", length(subcols_lig), " colours"))
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print(paste0("Colour palette generated for my_grp_r: ", length(subcolsR_lig), " colours"))
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####################################################################
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# Data for logoplots
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####################################################################
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