added corr_plots.R to generate corr plots by adding source data in get_plotting_dfs.R and tested with cmd
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scripts/plotting/corr_plots.R
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scripts/plotting/corr_plots.R
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#!/usr/bin/env Rscript
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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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spec = matrix(c(
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"drug" , "d", 1, "character",
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"gene" , "g", 1, "character",
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"data_file1" , "fa", 2, "character",
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"data_file2" , "fb", 2, "character"
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), byrow = TRUE, ncol = 4)
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opt = getopt(spec)
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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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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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#===========
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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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# PS
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corr_ps = "corr_PS.svg"
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plot_corr_ps = paste0(plotdir,"/", corr_ps)
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corr_ps_all = "corr_PS_all.svg"
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plot_corr_ps_all = paste0(plotdir,"/", corr_ps_all)
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# LIG
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corr_lig = "corr_LIG.svg"
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plot_corr_lig = paste0(plotdir,"/", corr_lig)
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corr_lig_all = "corr_LIG_all.svg"
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plot_corr_lig_all = paste0(plotdir,"/", corr_lig_all)
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##############################################################################
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foo = corr_ps_df3
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#foo2 = corr_ps_df2
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bar = corr_lig_df3
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#bar2 = corr_lig_df2
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#================================
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# Data for Correlation plots: PS
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#================================
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# subset data to generate pairwise correlations
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cols_to_select = c("DUET"
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, "Foldx"
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, "Log (OR)"
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, "-Log (P)"
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, "MAF"
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, "duet_outcome"
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, drug)
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corr_data_ps = foo[names(foo)%in%cols_to_select]
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length(cols_to_select)
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colnames(corr_data_ps)
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start = 1
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end = which(colnames(corr_data_ps) == drug); end # should be the last column
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offset = 1
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my_corr_ps = corr_data_ps[start:(end - offset)]
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head(my_corr_ps)
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#---------------------
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# Corr plot PS: short
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# data: corr_ps_df3
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# cols: 7
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#---------------------
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cat("Corr plot PS DUET with coloured dots:", plot_corr_ps)
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svg(plot_corr_ps, width = 15, height = 15)
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pairs.panels(my_corr_ps[1:(length(my_corr_ps)-1)]
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, method = "spearman" # correlation method
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, hist.col = "grey" ##00AFBB
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, density = TRUE # show density plots
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, ellipses = F # show correlation ellipses
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, stars = T
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, rug = F
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, breaks = "Sturges"
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, show.points = T
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, bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_ps$duet_outcome))] # foldx colours are reveresed
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, pch = 21 # for bg
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, jitter = T
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, alpha = 1
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, cex = 1.8
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, cex.axis = 2
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, cex.labels = 4
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, cex.cor = 1
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, smooth = F
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)
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dev.off()
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corr_ps_rho = corr.test(my_corr_ps[1:5], method = "spearman")$r
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corr_ps_p = corr.test(my_corr_ps[1:5], method = "spearman")$p
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#---------------------
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# Corr plot PS: ALL
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# data: corr_ps_df3
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# cols: 10
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#---------------------
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end_ps_all = which(colnames(foo) == drug); end_ps_all # should be the last column
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my_corr_ps_all = foo[start:(end_ps_all - offset)]
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cols_to_drop = "Mutation"
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my_corr_ps_all = my_corr_ps_all[, !(names(my_corr_ps_all)%in%cols_to_drop)]
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head(my_corr_ps_all)
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length(colnames(my_corr_ps_all))
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cat("Corr plot PS DUET with coloured dots:", plot_corr_ps_all)
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svg(plot_corr_ps_all, width = 15, height = 15)
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pairs.panels(my_corr_ps_all[1:(length(my_corr_ps_all)-1)]
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, method = "spearman" # correlation method
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, hist.col = "grey" ##00AFBB
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, density = TRUE # show density plots
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, ellipses = F # show correlation ellipses
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, stars = T
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, rug = F
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, breaks = "Sturges"
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, show.points = T
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, bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_ps_all$duet_outcome))] # foldx colours are reveresed
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, pch = 21 # for bg
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, jitter = T
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, alpha = 1
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, cex = 1.5
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, cex.axis = 2
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, cex.labels = 2.5
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, cex.cor = 1
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, smooth = F
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)
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dev.off()
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#==================================
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# Data for Correlation plots: LIG
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#==================================
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cols_to_select_lig = c("Ligand Affinity"
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, "Log (OR)"
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, "-Log (P)"
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, "MAF"
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, "ligand_outcome"
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, drug)
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corr_data_lig = bar[names(bar)%in%cols_to_select_lig]
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length(cols_to_select_lig)
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colnames(corr_data_lig)
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start_lig = 1
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end_lig = which(colnames(corr_data_lig) == drug); end_lig # should be the last column
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offset_lig = 1
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my_corr_lig = corr_data_lig[start_lig:(end_lig-offset_lig)]
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head(my_corr_lig)
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#---------------------
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# Corr plot LIG: short
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# data: corr_lig_df3
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# cols: 7
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#---------------------
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cat("Corr LIG plot with coloured dots:", plot_corr_lig)
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svg(plot_corr_lig, width = 15, height = 15)
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pairs.panels(my_corr_lig[1:(length(my_corr_lig)-1)]
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, method = "spearman" # correlation method
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, hist.col = "grey" ##00AFBB
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, density = TRUE # show density plots
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, ellipses = F # show correlation ellipses
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, stars = T
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, rug = F
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, breaks = "Sturges"
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, show.points = T
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, bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_lig$ligand_outcome))]
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, pch = 21 # for bg
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, jitter = T
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, cex = 2
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, cex.axis = 2
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, cex.labels = 4
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, cex.cor = 1
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, smooth = F
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)
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dev.off()
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corr_lig_rho = corr.test(my_corr_lig[1:4], method = "spearman")$r
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corr_lig_p = corr.test(my_corr_lig[1:4], method = "spearman")$p
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#---------------------
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# Corr plot LIG: ALL
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# data: corr_lig_df3
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# cols: 9
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#---------------------
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end_lig_all = which(colnames(bar) == drug); end_lig_all # should be the last column
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my_corr_lig_all = bar[start_lig:(end_lig_all - offset_lig)]
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cols_to_drop = "Mutation"
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my_corr_lig_all = my_corr_lig_all[, !(names(my_corr_lig_all)%in%cols_to_drop)]
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head(my_corr_lig_all)
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length(colnames(my_corr_lig_all))
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cat("Corr plot LIG with coloured dots:", plot_corr_lig_all)
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svg(plot_corr_lig_all, width = 15, height = 15)
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pairs.panels(my_corr_lig_all[1:(length(my_corr_lig_all)-1)]
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, method = "spearman" # correlation method
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, hist.col = "grey" ##00AFBB
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, density = TRUE # show density plots
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, ellipses = F # show correlation ellipses
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, stars = T
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, rug = F
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, breaks = "Sturges"
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, show.points = T
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, bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_lig_all$ligand_outcome))] # foldx colours are reveresed
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, pch = 21 # for bg
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, jitter = T
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, alpha = 1
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, cex = 1.5
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, cex.axis = 2
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, cex.labels = 2.2
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, cex.cor = 1
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, smooth = F
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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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