447 lines
14 KiB
R
447 lines
14 KiB
R
#!/usr/bin/env Rscript
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#########################################################
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# TASK: producing histogram of AF
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# basic
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# basic
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#########################################################
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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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library(ggplot2)
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library(data.table)
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library(dplyr)
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library(plyr)
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#source("plotting_data.R")
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source("combining_dfs_plotting.R")
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# clear excess variable
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rm(my_df, upos, dup_muts, my_df_u_lig)
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#=======================================================================
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#=======
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# output
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#=======
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# plot 1
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hist_af_muts = "hist_mutations_AF.svg"
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plot_hist_af_muts = paste0(plotdir,"/", hist_af_muts)
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# plot 2
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hist_or_muts = "hist_mutations_OR.svg"
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plot_hist_or_muts = paste0(plotdir,"/", hist_or_muts)
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# plot 3
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hist_af_muts_sample = "hist_af_muts_sample_combined.svg"
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plot_hist_af_muts_sample = paste0(plotdir,"/", hist_af_muts_sample)
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# plot 4
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hist_af_or = "hist_af_or_combined.svg"
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plot_hist_af_or = paste0(plotdir,"/", hist_af_or)
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# plot 5
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af_or_combined_med = "hist_bp_muts_combined_median.svg"
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plot_af_or_combined_med = paste0(plotdir, "/", af_or_combined_med)
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# plot 6: without median line on hist
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af_or_combined = "hist_bp_muts_combined.svg"
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plot_af_or_combined = paste0(plotdir, "/", af_or_combined)
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#=======================================================================
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merged_df3_comp$mutation_info_labels = ifelse(merged_df3_comp$mutation_info == dr_muts_col, "DM", "OM")
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table(merged_df3_comp$mutation_info_labels)
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table(merged_df3_comp$mutation_info) == table(merged_df3_comp$mutation_info_labels)
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merged_df2_comp$mutation_info_labels = ifelse(merged_df2_comp$mutation_info == dr_muts_col, "DM", "OM")
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table(merged_df2_comp$mutation_info_labels)
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table(merged_df2_comp$mutation_info) == table(merged_df2_comp$mutation_info_labels)
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#================
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# Data for plots
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#================
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# REASSIGNMENT as necessary
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df = my_df_u
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df3 = merged_df3_comp
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# Contains duplicated samples, so you need to remove that for AF hist
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merged_df2_comp_u = merged_df2_comp[!duplicated(merged_df2_comp$id),]
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if ( nrow(merged_df2_comp_u) == length(unique(merged_df2_comp$id)) ){
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cat("PASS: duplicated samples ommitted. Assiging for plotting...")
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df2 = merged_df2_comp_u
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}else{
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cat("FAIL: duplicated samples could not be ommitted. Length mismatch"
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, "Expected nrows:", length(unique(merged_df2_comp$id))
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, "Got nrows:", nrow(merged_df2_comp_u))
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}
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df2_af_median <- ddply(df2, "mutation_info_labels", summarise, grp.median = median(af, na.rm = T))
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head(df2_af_median)
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#=======================================================================
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#****************
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# Plot 1: AF distribution: mutations
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#****************
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svg(plot_hist_af_muts)
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print(paste0("plot1 filename:", plot_hist_af_muts))
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#--------------
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# start plot 1
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#--------------
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#par(mar=c(b, l, t, r))
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par(mar=c(5,6,1,0))
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hist(df3$af
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, freq = T
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, breaks = 30
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, xlab = "Minor Allele Frequency"
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, ylab = "Frequency"
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, main = ""
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, cex.lab = 1.7
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, cex.axis = 1.5
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, cex.main = 1.5
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, cex.sub = 1.5)
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dev.off()
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#****************
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# Plot 2: AF distribution: samples
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#****************
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#--------------
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# start plot 2
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#--------------
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#par(mar=c(b, l, t, r))
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par(mar=c(5,6,1,0))
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hist(df2$af
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, freq = T
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, breaks = 30
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, xlab = "Minor Allele Frequency"
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, ylab = "Frequency"
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, main = ""
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, cex.lab = 1.7
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, cex.axis = 1.5
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, cex.main = 1.5
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, cex.sub = 1.5)
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#****************
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# Plot 3: OF distribution: mutations
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#****************
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svg(plot_hist_or_muts)
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print(paste0("plot3 filename:", plot_hist_or_muts))
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#--------------
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# start plot 3
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#--------------
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#par(mar=c(b, l, t, r))
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par(mar=c(5,6,1,0))
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hist(df3$or_mychisq
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, freq = T
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, breaks = 30
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, xlab = "Odds Ratio"
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, ylab = "Frequency"
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, main = ""
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, cex.lab = 1.7
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, cex.axis = 1.5
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, cex.main = 1.5
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, cex.sub = 1.5)
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dev.off()
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#====================================================================
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#==========
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# combine and output
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#==========
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#--------------
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# combine: af and or
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#-------------
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svg(plot_hist_af_or, width = 10, height = 8)
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print(paste0("plot3 filename:", plot_hist_af_or))
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#par(bty = "l")
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par(mfrow=c(2,1))
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par(mar=c(4.5, 5.5, 2, 0))
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hist(df3$af
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, freq = T
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, breaks = 30
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, xlab = "Minor Allele Frequency (MAF)"
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, ylab = "Frequency"
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, main = ""
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, cex.lab = 1.3
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, cex.axis = 1.3
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, cex.main = 1.5
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, cex.sub = 1.5)
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# print the overall labels
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mtext(expression(bold('(a)')), side = 3, adj = -0.1, cex = 1.8)
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hist(df3$or_mychisq
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, freq = T
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, breaks = 30
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, xlab = "Odds Ratio (OR)"
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, ylab = "Frequency"
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, main = ""
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, cex.lab = 1.3
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, cex.axis = 1.3
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, cex.main = 1.5
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, cex.sub = 1.5)
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# print the overall labels
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mtext(expression(bold('(b)')), side = 3, adj = -0.1, cex = 1.8)
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dev.off()
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#--------------
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# combine: af (mutations and samples)
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#-------------
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svg(plot_hist_af_muts_sample, width = 10, height = 8)
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print(paste0("plot3 filename:", plot_hist_af_muts_sample))
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#par(bty = "l")
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par(mfrow = c(1,2))
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par(mar=c(4.5, 5.5, 2, 0))
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hist(df3$af
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, freq = T
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, breaks = 30
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, xlab = "Minor Allele Frequency (MAF)"
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, ylab = "Frequency"
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, main = paste0(nrow(df3),"_pnca_mutations")
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, cex.lab = 1.3
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, cex.axis = 1.3
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, cex.main = 1.5
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, cex.sub = 1.5)
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hist(df2$af
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, freq = T
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, breaks = 30
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, xlab = "Minor Allele Frequency (MAF)"
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, ylab = "Frequency"
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, main = paste0(nrow(df2),"_pnca_samples")
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, cex.lab = 1.3
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, cex.axis = 1.3
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, cex.main = 1.5
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, cex.sub = 1.5)
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dev.off()
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########################################################
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#############
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# ggplots
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#############
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#library(plyr)
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df3_af_median <- ddply(df3, "mutation_info_labels", summarise, grp.median = median(af, na.rm = T))
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head(df3_af_median)
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my_ats = 15 # axis text size
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my_als = 18 # axis label size
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theme_set(theme_grey())
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g_af_hist = ggplot(df3, aes(x = af)) +
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geom_histogram(colour = "white") +
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats)
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#, axis.title.y = element_blank()
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, axis.title.x = element_text(size = my_ats)
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#, axis.title.x = element_blank()
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, axis.title.y = element_text(size = my_ats)
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, axis.ticks.y = element_blank()
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, plot.title = element_blank())+
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labs(y = "Count"
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, x = "Minor Allele Frequency"
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)
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g_af_hist
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#=====================================================================
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df3_af_median <- ddply(df3, "mutation_info_labels", summarise, grp.median = median(af, na.rm = T))
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head(df3_af_median)
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g_af_hist_col = ggplot(df3, aes(x = af, fill = mutation_info_labels)) +
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geom_histogram(position = "stack") +
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scale_fill_manual(values = c("#E69F00", "#999999")) +
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats)
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#, axis.title.y = element_blank()
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, axis.title.x = element_text(size = my_ats)
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#, axis.title.x = element_blank()
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, axis.title.y = element_text(size = my_ats)
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, axis.ticks.y = element_blank()
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, plot.title = element_blank())+
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labs(y = "Count"
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, x = "Minor Allele Frequency"
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)
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g_af_hist_col
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g_af_hist_col_med = g_af_hist_col + geom_vline(data = df3_af_median, aes(xintercept = grp.median),
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linetype = "dashed")
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g_af_hist_col_med
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#=====================================================================
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g_af_mutinfo = ggplot(df3, aes(x = af
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, fill = mutation_info_labels)) +
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scale_fill_manual(values = c("#E69F00", "#999999")) +
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geom_histogram() +
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facet_grid(mutation_info_labels ~ ., scales = "free") +
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#facet_wrap(mutation_info_labels ~ ., scales = "free") +
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats)
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, axis.title.x = element_text(size = my_ats)
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#, axis.title.y = element_blank()
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, axis.title.y = element_text(size = my_ats)
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, axis.ticks.y = element_blank()
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, plot.title = element_text(size = my_ats+5, face ="bold", hjust = 0.5)
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#, strip.text = element_text(size = my_als)
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, strip.text = element_blank()
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, strip.background = element_blank()
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, legend.text = element_text(size = my_als-4)
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, legend.title = element_text(size = my_als-4)
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, legend.position = c(0.8, 0.9)) +
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labs(title = "Minor Allele Frequency (MAF)"
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, x = "MAF"
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, y = "Count"
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, fill = "Mutation class")
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g_af_mutinfo
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g_af_mutinfo_med = g_af_mutinfo + geom_vline(data = df3_af_median, aes(xintercept = grp.median),
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linetype = "dashed")
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g_af_mutinfo_med
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#=====================================================================
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my_comparisons <- list( c("DM", "OM") )
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g_af_bp = ggplot(df3, aes(x = mutation_info_labels
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, y = af
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, fill = mutation_info_labels))+
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scale_fill_manual(values = c("#E69F00", "#999999")) +
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geom_boxplot()+
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats)
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, axis.title.x = element_text(size = my_ats)
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#, axis.title.y = element_blank()
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, axis.title.y = element_text(size = my_ats)
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, axis.ticks.y = element_blank()
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, plot.title = element_blank()
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, strip.text = element_text(size = my_als)
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, legend.text = element_text(size = my_als-4)
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, legend.title = element_text(size = my_als-4)
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, legend.position = "none") +
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labs(y = "MAF"
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, x = ""
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, fill = "Mutation class")
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g_af_bp_stats = g_af_bp + stat_compare_means(comparisons = my_comparisons
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, method = "wilcox.test"
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, paired = FALSE
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#, label = "p.format"
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, label = "p.signif")
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g_af_bp_stats
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######################################################################
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# OR
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######################################################################
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df3_or_median <- ddply(df3, "mutation_info_labels", summarise, grp.median = median(or_mychisq, na.rm = T))
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head(df3_or_median)
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g_or_mutinfo = ggplot(df3, aes(x = or_mychisq
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, fill = mutation_info_labels)) +
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scale_fill_manual(values = c("#E69F00", "#999999")) +
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geom_histogram() +
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facet_grid(mutation_info_labels ~ ., scales = "free") +
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#facet_wrap(mutation_info_labels ~ ., scales = "free") +
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats)
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, axis.title.x = element_text(size = my_ats)
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, axis.title.y = element_text(size = my_ats)
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#, axis.title.y = element_blank()
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, axis.ticks.y = element_blank()
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, plot.title = element_text(size = my_ats+5, face ="bold", hjust = 0.5)
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#, strip.text = element_text(size = my_als)
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, strip.text = element_blank()
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, strip.background = element_blank()
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, legend.text = element_text(size = my_als-4)
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, legend.title = element_text(size = my_als-4)
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, legend.position = c(0.8, 0.9))+
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labs(title = "Odds Ratio (OR)"
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, x = "OR"
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, y = "Count"
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, fill = "Mutation class")
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g_or_mutinfo
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g_or_mutinfo_med = g_or_mutinfo + geom_vline(data = df3_or_median, aes(xintercept = grp.median),
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linetype = "dashed")
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g_or_mutinfo_med
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#=====================================================================
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g_or_bp = ggplot(df3, aes(x = mutation_info_labels
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, y = or_mychisq
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, fill = mutation_info_labels))+
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scale_fill_manual(values = c("#E69F00", "#999999")) +
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geom_boxplot()+
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats)
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, axis.title.x = element_text(size = my_ats)
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#, axis.title.y = element_blank()
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, axis.title.y = element_text(size = my_ats)
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, axis.ticks.y = element_blank()
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, plot.title = element_blank()
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, strip.text = element_text(size = my_als)
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, legend.text = element_text(size = my_als-4)
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, legend.title = element_text(size = my_als-4)
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, legend.position = "none") +
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labs(y = "OR"
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, x = ""
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, fill = "Mutation class")
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g_or_bp_stats = g_or_bp + stat_compare_means(comparisons = my_comparisons
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, method = "wilcox.test"
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, paired = FALSE
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#, label = "p.format"
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, label = "p.signif")
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g_or_bp_stats
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############################################################################
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#==============================
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# combine plots for outputs
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#==============================
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#------------------------------------
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# Plot 1: hist withOUT median line
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#------------------------------------
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# combined plots without median
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#print(paste0("plot combined filename:", plot_af_or_combined))
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#svg(plot_af_or_combined, width = 16, height = 9)
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c_combined = cowplot::plot_grid(g_af_mutinfo
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, g_af_bp_stats
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, g_or_mutinfo
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, g_or_bp_stats
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, nrow = 2
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, labels = c("(a)", "(b)", "(c)", "(d)")
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, rel_widths = c(2/3, 1/3)
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, label_size = 20)
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#print(c_combined)
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#dev.off()
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#-------------------------------
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# Plot 2: hist WITH median line
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#-------------------------------
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print(paste0("plot combined filename:", plot_af_or_combined_med))
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svg(plot_af_or_combined_med, width = 16, height = 9)
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c_combined_med = cowplot::plot_grid(g_af_mutinfo_med
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, g_af_bp_stats
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, g_or_mutinfo_med
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, g_or_bp_stats
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, nrow = 2
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, labels = c("(a)", "(b)", "(c)", "(d)")
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, rel_widths = c(3/4, 1/4)
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, label_size = 20)
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print(c_combined_med)
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dev.off()
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######################################################################
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