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366
scripts/plotting/plotting_thesis/corr_plots_thesis_ggpairs.R
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366
scripts/plotting/plotting_thesis/corr_plots_thesis_ggpairs.R
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#!/usr/bin/env Rscript
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#source("~/git/LSHTM_analysis/config/alr.R")
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source("~/git/LSHTM_analysis/config/embb.R")
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#source("~/git/LSHTM_analysis/config/katg.R")
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#source("~/git/LSHTM_analysis/config/gid.R")
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#source("~/git/LSHTM_analysis/config/pnca.R")
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#source("~/git/LSHTM_analysis/config/rpob.R")
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# get plottting dfs
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source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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source("~/git/LSHTM_analysis/scripts/plotting/plotting_colnames.R")
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####################################################
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# ggpairs wrapper
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my_gg_pairs=function(plot_df){
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ggpairs(plot_df, columns = 1:(ncol(plot_df)-1),
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upper = list(continuous = wrap('cor',
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method = "spearman",
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title="ρ",
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digits=2,
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title_args=c(colour="black")
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)
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),
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lower = list(
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continuous = wrap("points", alpha = 0.7, size=0.5),
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combo = wrap("dot", alpha = 0.7, size=0.5)
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),
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aes(colour = factor(ifelse(plot_df$dst_mode==0, "S", "R")), alpha = 0.5),
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title="Stability") +
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scale_colour_manual(values = c("red", "blue")) +
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scale_fill_manual(values = c("red", "blue")) +
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theme(
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text = element_text(size=12, face="bold")
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)
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}
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#=======
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# output
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#=======
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outdir_images = paste0("~/git/Writing/thesis/images/results/", tolower(gene), "/")
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#=======
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# Input
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#=======
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merged_df3 = as.data.frame(merged_df3)
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corr_plotdf = corr_data_extract(merged_df3
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, gene = gene
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, drug = drug
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, extract_scaled_cols = F)
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colnames(corr_plotdf)
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if (all(colnames(corr_df_m3_f) == colnames(corr_plotdf))){
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cat("PASS: corr plot colnames match for dashboard")
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}else{
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stop("Abort: corr plot colnames DO NOT match for dashboard")
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}
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#corr_plotdf = corr_df_m3_f #for downstream code
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aff_dist_cols = colnames(corr_plotdf)[grep("Dist", colnames(corr_plotdf))]
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aff_dist_cols
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static_cols = c("Log10(MAF)"
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, "Log10(OR)"
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#, "-Log10(P)"
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)
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#================
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# stability
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#================
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#affinity_dist_colnames# lIg DIst and ppi Di
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corr_ps_colnames = c(static_cols
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, "DUET"
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, "FoldX"
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, "DeepDDG"
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, "Dynamut2"
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, aff_dist_cols
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, "dst_mode")
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if (all(corr_ps_colnames%in%colnames(corr_plotdf))){
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cat("PASS: all colnames exist for correlation")
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}else{
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stop("Abort: all colnames DO NOT exist for correlation")
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}
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corr_df_ps = corr_plotdf[, corr_ps_colnames]
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complete_obs_ps = nrow(corr_df_ps) - sum(is.na(corr_df_ps$`Log(OR)`))
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cat("\nComplete muts for Conservation for", gene, ":", complete_obs_ps)
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color_coln = which(colnames(corr_df_ps) == "dst_mode")
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#end = which(colnames(corr_df_ps) == drug)
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#ncol_omit = 2
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#corr_end = end-ncol_omit
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corr_end = color_coln-1
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#------------------------
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# Output: stability corrP
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#------------------------
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corr_psP = paste0(outdir_images
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,tolower(gene)
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,"_corr_stability.svg" )
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cat("Corr plot stability with coloured dots:", corr_psP)
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svg(corr_psP, width = 15, height = 15)
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my_corr_pairs(corr_data_all = corr_df_ps
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, corr_cols = colnames(corr_df_ps[1:corr_end])
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, corr_method = "spearman"
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, colour_categ_col = colnames(corr_df_ps[color_coln]) #"dst_mode"
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, categ_colour = c("red", "blue")
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, density_show = F
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, hist_col = "coral4"
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, dot_size = 1.6
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, ats = 1.5
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, corr_lab_size =2.5
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, corr_value_size = 1)
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dev.off()
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#===============
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# CONSERVATION
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#==============
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corr_conservation_cols = c( static_cols
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, "ConSurf"
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, "SNAP2"
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, "PROVEAN"
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, aff_dist_cols
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, "dst_mode"
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, drug)
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if (all(corr_conservation_cols%in%colnames(corr_plotdf))){
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cat("PASS: all colnames exist for ConSurf-correlation")
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}else{
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stop("Abort: all colnames DO NOT exist for ConSurf-correlation")
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}
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corr_df_cons = corr_plotdf[, corr_conservation_cols]
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complete_obs_cons = nrow(corr_df_cons) - sum(is.na(corr_df_cons$`Log(OR)`))
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cat("\nComplete muts for Conservation for", gene, ":", complete_obs_cons)
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color_coln = which(colnames(corr_df_cons) == "dst_mode")
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# end = which(colnames(corr_df_cons) == drug)
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# ncol_omit = 2
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# corr_end = end-ncol_omit
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corr_end = color_coln-1
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#---------------------------
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# Output: Conservation corrP
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#----------------------------
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corr_consP = paste0(outdir_images
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,tolower(gene)
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,"_corr_conservation.svg" )
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cat("Corr plot conservation coloured dots:", corr_consP)
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svg(corr_consP, width = 10, height = 10)
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my_corr_pairs(corr_data_all = corr_df_cons
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, corr_cols = colnames(corr_df_cons[1:corr_end])
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, corr_method = "spearman"
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, colour_categ_col = colnames(corr_df_cons[color_coln]) #"dst_mode"
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, categ_colour = c("red", "blue")
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, density_show = F
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, hist_col = "coral4"
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, dot_size =1.1
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, ats = 1.5
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, corr_lab_size = 1.8
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, corr_value_size = 1)
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dev.off()
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#####################################################
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#DistCutOff = 10
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#LigDist_colname # = "ligand_distance" # from globals
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#ppi2Dist_colname = "interface_dist"
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#naDist_colname = "TBC"
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#####################################################
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#================
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# ligand affinity
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#================
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corr_df_lig = corr_plotdf[corr_plotdf["Lig-Dist"]<DistCutOff,]
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corr_lig_colnames = c(static_cols
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, "mCSM-lig"
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, "mmCSM-lig"
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, "dst_mode")
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#, drug)
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if (all(corr_lig_colnames%in%colnames(corr_plotdf))){
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cat("PASS: all colnames exist for Lig-correlation")
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}else{
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stop("Abort: all colnames DO NOT exist for Lig-correlation")
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}
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corr_df_lig = corr_plotdf[, corr_lig_colnames]
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complete_obs_lig = nrow(corr_df_lig) - sum(is.na(corr_df_lig$`Log(OR)`))
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cat("\nComplete muts for lig affinity for", gene, ":", complete_obs_lig)
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color_coln = which(colnames(corr_df_lig) == "dst_mode")
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# end = which(colnames(corr_df_lig) == drug)
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# ncol_omit = 2
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# corr_end = end-ncol_omit
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corr_end = color_coln-1
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#------------------------
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# Output: ligand corrP
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#------------------------
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corr_ligP = paste0(outdir_images
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,tolower(gene)
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,"_corr_lig.svg" )
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cat("Corr plot affinity with coloured dots:", corr_ligP)
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svg(corr_ligP, width = 10, height = 10)
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my_corr_pairs(corr_data_all = corr_df_lig
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, corr_cols = colnames(corr_df_lig[1:corr_end])
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, corr_method = "spearman"
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, colour_categ_col = colnames(corr_df_lig[color_coln]) #"dst_mode"
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, categ_colour = c("red", "blue")
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, density_show = F
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, hist_col = "coral4"
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, dot_size = 2
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, ats = 1.5
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, corr_lab_size =3
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, corr_value_size = 1)
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dev.off()
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####################################################
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#================
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# ppi2 affinity
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#================
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if (tolower(gene)%in%geneL_ppi2){
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corr_df_ppi2 = corr_plotdf[corr_plotdf["PPI-Dist"]<DistCutOff,]
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corr_ppi2_colnames = c(static_cols
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, "mCSM-PPI2"
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, "dst_mode"
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, drug)
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if (all(corr_ppi2_colnames%in%colnames(corr_plotdf))){
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cat("PASS: all colnames exist for mcsm-ppi2 correlation")
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}else{
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stop("Abort: all colnames DO NOT exist for mcsm-ppi2 correlation")
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}
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corr_df_ppi2 = corr_plotdf[, corr_ppi2_colnames]
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complete_obs_ppi2 = nrow(corr_df_ppi2) - sum(is.na(corr_df_ppi2$`Log(OR)`))
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cat("\nComplete muts for ppi2 affinity for", gene, ":", complete_obs_ppi2)
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color_coln = which(colnames(corr_df_ppi2) == "dst_mode")
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# end = which(colnames(corr_df_ppi2) == drug)
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# ncol_omit = 2
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# corr_end = end-ncol_omit
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corr_end = color_coln-1
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#------------------------
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# Output: ppi2 corrP
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#------------------------
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corr_ppi2P = paste0(outdir_images
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,tolower(gene)
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,"_corr_ppi2.svg" )
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cat("Corr plot ppi2 with coloured dots:", corr_ppi2P)
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svg(corr_ppi2P, width = 10, height = 10)
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my_corr_pairs(corr_data_all = corr_df_ppi2
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, corr_cols = colnames(corr_df_ppi2[1:corr_end])
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, corr_method = "spearman"
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, colour_categ_col = colnames(corr_df_ppi2[color_coln]) #"dst_mode"
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, categ_colour = c("red", "blue")
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, density_show = F
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, hist_col = "coral4"
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, dot_size = 2
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, ats = 1.5
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, corr_lab_size = 3
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, corr_value_size = 1)
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dev.off()
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}
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# FIXME: ADD distance
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#==================
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# mCSSM-NA affinity
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#==================
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#================
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# NA affinity
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#================
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if (tolower(gene)%in%geneL_na){
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corr_df_na = corr_df_na[corr_df_na["NA-Dist"]<DistCutOff,]
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corr_na_colnames = c(static_cols
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, "mCSM-NA"
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, "dst_mode"
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, drug)
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if (all(corr_na_colnames%in%colnames(corr_plotdf))){
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cat("PASS: all colnames exist for mcsm-NA-correlation")
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}else{
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stop("Abort: all colnames DO NOT exist for mcsm-NA-correlation")
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}
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corr_na_colnames%in%colnames(corr_plotdf)
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corr_df_na = corr_plotdf[, corr_na_colnames]
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complete_obs_na = nrow(corr_df_na) - sum(is.na(corr_df_na$`Log(OR)`))
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cat("\nComplete muts for NA affinity for", gene, ":", complete_obs_na)
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color_coln = which(colnames(corr_df_na) == "dst_mode")
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# end = which(colnames(corr_df_na) == drug)
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# ncol_omit = 2
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# corr_end = end-ncol_omit
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corr_end = color_coln-1
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#------------------------
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# Output: mCSM-NA corrP
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#------------------------
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corr_naP = paste0(outdir_images
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,tolower(gene)
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,"_corr_na.svg" )
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cat("Corr plot mCSM-NA with coloured dots:", corr_naP)
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svg(corr_naP, width = 10, height = 10)
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my_corr_pairs(corr_data_all = corr_df_na
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, corr_cols = colnames(corr_df_na[1:corr_end])
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, corr_method = "spearman"
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, colour_categ_col = colnames(corr_df_na[color_coln]) #"dst_mode"
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, categ_colour = c("red", "blue")
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, density_show = F
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, hist_col = "coral4"
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, dot_size = 2
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, ats = 1.5
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, corr_lab_size = 3
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, corr_value_size = 1)
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dev.off()
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}
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####################################################
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#===============
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#ggpairs:
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#================
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#corr_df_ps$dst_mode = ifelse(corr_df_cons$dst_mode=="1", "R", "S")
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corr_plotting_df = corr_df_ps
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svg('~/tmp/foo.svg',
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width=10,
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height=10,
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units="in",
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res=300)
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my_gg_pairs(corr_plotting_df)
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dev.off()
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png('~/tmp/foo.png',
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width=10,
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height=10,
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units="in",
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res=300)
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my_gg_pairs(corr_plotting_df)
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dev.off()
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#
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49
scripts/plotting/plotting_thesis/gg_pairs.R
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49
scripts/plotting/plotting_thesis/gg_pairs.R
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# Tweak for layout, fonts, and text sizes.
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#svg('~/tmp/foo.svg', width=10, height=10, )
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# Set the width/height to inches for print. 300 dpi is reasonably ok for "draft"
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# output. To raise quality while preserving sanity, increase 'res' and
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# DO NOT alter font/point/line sizes
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#- [X] Black text for "Corr:" or replace with Rho symbol
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#- [X] 0/1 == R/S
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#- [X] "rho" symbol instead of "Corr:" text
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#- [X] Dot size a bit smaller
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#- [X] Plot lines slightly thinner
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#
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#
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png('~/tmp/foo.png',
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width=10,
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height=10,
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units="in",
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res=300)
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#
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corr_plotting_df = corr_df_ps
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ggpairs(corr_plotting_df, columns = 1:(ncol(corr_plotting_df)-1),
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upper = list(continuous = wrap('cor',
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method = "spearman",
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title="ρ",
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digits=2,
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title_args=c(colour="black")
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)
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),
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lower = list(
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continuous = wrap("points", alpha = 0.7, size=0.5),
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combo = wrap("dot", alpha = 0.7, size=0.5)
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),
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aes(colour = factor(ifelse(corr_plotting_df$dst_mode==0, "S", "R")), alpha = 0.5),
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title="Stability") +
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scale_colour_manual(values = c("red", "blue")) +
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scale_fill_manual(values = c("red", "blue")) +
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theme(
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text = element_text(size=12, face="bold")
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)
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dev.off()
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#Check all plots with LSHTM_analysis/scripts/plotting/plotting_colnames.R
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144
scripts/plotting/plotting_thesis/gg_pairs_all.R
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144
scripts/plotting/plotting_thesis/gg_pairs_all.R
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source("~/git/LSHTM_analysis/config/embb.R")
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source("~/git/LSHTM_analysis/scripts/plotting/plotting_colnames.R")
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source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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my_gg_pairs=function(plot_df){
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ggpairs(plot_df,
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columns = 1:(ncol(plot_df)-1),
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upper = list(
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continuous = wrap('cor',
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method = "spearman",
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title="ρ",
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digits=2,
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justify_labels = "left",
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title_args=c(colour="black")
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)
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),
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lower = list(
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continuous = wrap("points",
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alpha = 0.7,
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size=0.5),
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combo = wrap("dot",
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alpha = 0.7,
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size=0.5)
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),
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aes(colour = factor(ifelse(plot_df$dst_mode==0,
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"S",
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"R") ),
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alpha = 0.5),
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title="Stability") +
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scale_colour_manual(values = c("red", "blue")) +
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scale_fill_manual(values = c("red", "blue")) +
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theme(text = element_text(size=12,
|
||||
face="bold") )
|
||||
}
|
||||
|
||||
DistCutOff = 10
|
||||
|
||||
merged_df3 = as.data.frame(merged_df3)
|
||||
corr_plotdf = corr_data_extract(merged_df3
|
||||
, gene = gene
|
||||
, drug = drug
|
||||
, extract_scaled_cols = F)
|
||||
|
||||
aff_dist_cols = colnames(corr_plotdf)[grep("Dist", colnames(corr_plotdf))]
|
||||
static_cols = c("Log10(MAF)"
|
||||
, "Log10(OR)")
|
||||
|
||||
corr_ps_colnames = c(static_cols
|
||||
, "DUET"
|
||||
, "FoldX"
|
||||
, "DeepDDG"
|
||||
, "Dynamut2"
|
||||
, aff_dist_cols
|
||||
, "dst_mode")
|
||||
corr_df_ps = corr_plotdf[, corr_ps_colnames]
|
||||
complete_obs_ps = nrow(corr_df_ps) - sum(is.na(corr_df_ps$`Log(OR)`))
|
||||
color_coln = which(colnames(corr_df_ps) == "dst_mode")
|
||||
corr_end = color_coln-1
|
||||
|
||||
# Plot #1
|
||||
plot_corr_df_ps = my_gg_pairs(corr_df_ps)
|
||||
|
||||
|
||||
corr_conservation_cols = c( static_cols
|
||||
, "ConSurf"
|
||||
, "SNAP2"
|
||||
, "PROVEAN"
|
||||
, aff_dist_cols
|
||||
, "dst_mode"
|
||||
)
|
||||
|
||||
corr_df_cons = corr_plotdf[, corr_conservation_cols]
|
||||
complete_obs_cons = nrow(corr_df_cons) - sum(is.na(corr_df_cons$`Log(OR)`))
|
||||
color_coln = which(colnames(corr_df_cons) == "dst_mode")
|
||||
corr_end = color_coln-1
|
||||
|
||||
# Plot #2
|
||||
|
||||
#my_gg_pairs(corr_df_cons)
|
||||
plot_corr_df_cons = my_gg_pairs(corr_df_cons)
|
||||
|
||||
|
||||
corr_df_lig = corr_plotdf[corr_plotdf["Lig-Dist"]<DistCutOff,]
|
||||
corr_lig_colnames = c(static_cols
|
||||
, "mCSM-lig"
|
||||
, "mmCSM-lig"
|
||||
, "dst_mode")
|
||||
|
||||
corr_df_lig = corr_plotdf[, corr_lig_colnames]
|
||||
|
||||
complete_obs_lig = nrow(corr_df_lig) - sum(is.na(corr_df_lig$`Log(OR)`))
|
||||
color_coln = which(colnames(corr_df_lig) == "dst_mode")
|
||||
corr_end = color_coln-1
|
||||
# Plot #3
|
||||
|
||||
#my_gg_pairs(corr_df_lig)
|
||||
plot_corr_df_lig = my_gg_pairs(corr_df_lig)
|
||||
|
||||
corr_df_ppi2 = corr_plotdf[corr_plotdf["PPI-Dist"]<DistCutOff,]
|
||||
corr_ppi2_colnames = c(static_cols
|
||||
, "mCSM-PPI2"
|
||||
, "dst_mode"
|
||||
)
|
||||
corr_df_ppi2 = corr_plotdf[, corr_ppi2_colnames]
|
||||
complete_obs_ppi2 = nrow(corr_df_ppi2) - sum(is.na(corr_df_ppi2$`Log(OR)`))
|
||||
color_coln = which(colnames(corr_df_ppi2) == "dst_mode")
|
||||
corr_end = color_coln-1
|
||||
|
||||
# NOTE: DELETE LOG OR FROM CORRELATION PLOTS!!!!!
|
||||
# NOTE: ALSO MAYBE DELETE DISTANCES AS WELL
|
||||
# NOTE: http://ggobi.github.io/ggally/reference/ggally_cor.html
|
||||
|
||||
# "***" if the p-value is < 0.001
|
||||
# "**" if the p-value is < 0.01
|
||||
# "*" if the p-value is < 0.05
|
||||
# "." if the p-value is < 0.10
|
||||
# "" otherwise
|
||||
#
|
||||
|
||||
# Plot #4
|
||||
#my_gg_pairs(corr_df_ppi2)
|
||||
plot_corr_df_ppi2 = my_gg_pairs(corr_df_ppi2)
|
||||
|
||||
|
||||
# corr_df_na = corr_df_na[corr_df_na["NA-Dist"]<DistCutOff,]
|
||||
# corr_na_colnames = c(static_cols
|
||||
# , "mCSM-NA"
|
||||
# , "dst_mode"
|
||||
# )
|
||||
#
|
||||
# corr_df_na = corr_plotdf[, corr_na_colnames]
|
||||
# complete_obs_na = nrow(corr_df_na) - sum(is.na(corr_df_na$`Log(OR)`))
|
||||
# color_coln = which(colnames(corr_df_na) == "dst_mode")
|
||||
# corr_end = color_coln-1
|
||||
#
|
||||
# # Plot #5
|
||||
# #my_gg_pairs(corr_df_na)
|
||||
# plot_corr_df_na = my_gg_pairs(corr_df_na)
|
||||
|
||||
|
||||
cowplot::plot_grid(ggmatrix_gtable(plot_corr_df_ps),ggmatrix_gtable(plot_corr_df_cons),
|
||||
ggmatrix_gtable(plot_corr_df_lig),ggmatrix_gtable(plot_corr_df_ppi2),
|
||||
nrow=2, ncol=2, rel_heights = 7,7,3,3)
|
||||
Loading…
Add table
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Reference in a new issue