LSHTM_analysis/scripts/plotting/hist_af_or_combined.R

359 lines
14 KiB
R

#!/usr/bin/env Rscript
#########################################################
# TASK: producing histogram of AF and OR
# output svgs
# 1) hist of af
# 2) hist of or
# 3) hist of af_or combined
# 4) hist of af: from muts and samples dfs combined (EXPLORATORY!)
# 5) hist and barplots for af_or combined with median line
# 6) hist and barplots for af_or combined withOUT median line (Turned OFF)
#########################################################
#=======================================================================
# working dir and loading libraries
getwd()
setwd("~/git/LSHTM_analysis/scripts/plotting")
getwd()
#source("Header_TT.R")
library(ggplot2)
library(data.table)
library(dplyr)
library(plyr)
#source("plotting_data.R")
source("combining_dfs_plotting.R")
#=======================================================================
#=======
# output
#=======
# plot: with median line on hist
af_or_combined_med = "hist_bp_muts_combined_median_labelled.svg"
plot_af_or_combined_med = paste0(plotdir, "/", af_or_combined_med)
# plot 6: without median line on hist
af_or_combined = "hist_bp_muts_combined.svg"
plot_af_or_combined = paste0(plotdir, "/", af_or_combined)
#=======================================================================
merged_df3_comp$mutation_info_labels = ifelse(merged_df3_comp$mutation_info == dr_muts_col, "DM", "OM")
table(merged_df3_comp$mutation_info_labels)
table(merged_df3_comp$mutation_info) == table(merged_df3_comp$mutation_info_labels)
sum(table(merged_df3_comp$mutation_info))
merged_df2_comp$mutation_info_labels = ifelse(merged_df2_comp$mutation_info == dr_muts_col, "DM", "OM")
table(merged_df2_comp$mutation_info_labels)
table(merged_df2_comp$mutation_info) == table(merged_df2_comp$mutation_info_labels)
sum(table(merged_df2_comp$mutation_info))
#================
# Data for plots
#================
# REASSIGNMENT as necessary
#df = my_df_u
df3 = merged_df3_comp
# Contains duplicated samples, so you need to remove that for AF hist
merged_df2_comp_u = merged_df2_comp[!duplicated(merged_df2_comp$id),]
if ( nrow(merged_df2_comp_u) == length(unique(merged_df2_comp$id)) ){
cat("PASS: duplicated samples ommitted. Assiging for plotting...")
df2 = merged_df2_comp_u
}else{
cat("FAIL: duplicated samples could not be ommitted. Length mismatch"
, "Expected nrows:", length(unique(merged_df2_comp$id))
, "Got nrows:", nrow(merged_df2_comp_u))
}
df2_af_median <- ddply(df2, "mutation_info_labels", summarise, grp.median = median(af, na.rm = T))
head(df2_af_median)
########################################################
#############
# ggplots
#############
my_ats = 15 # axis text size
my_als = 18 # axis label size
#theme_set(theme_grey())
#-----------
# AF: hist
#-----------
g_af_hist = ggplot(df3, aes(x = af)) +
geom_histogram(colour = "white") +
theme(axis.text.x = element_text(size = my_ats)
, axis.text.y = element_text(size = my_ats)
#, axis.title.y = element_blank()
, axis.title.x = element_text(size = my_ats)
#, axis.title.x = element_blank()
, axis.title.y = element_text(size = my_ats)
, axis.ticks.y = element_blank()
, plot.title = element_blank())+
#, plot.title = element_text(size = my_ats+5, face ="bold", hjust = 0.5))+
labs(title = "Minor Allele Frequency (MAF)"
, x = "MAF"
, y = "Count")
g_af_hist
#=====================================================================
#------------------------
# AF: hist coloured by
# mutation class in the
# same graph
#---------------------
#library(plyr)
df3_af_median <- ddply(df3, "mutation_info_labels", summarise, grp.median = median(af, na.rm = T))
head(df3_af_median)
g_af_hist_col = ggplot(df3, aes(x = af, fill = mutation_info_labels)) +
geom_histogram(position = "stack") +
scale_fill_manual(values = c("#E69F00", "#999999")) +
theme(axis.text.x = element_text(size = my_ats)
, axis.text.y = element_text(size = my_ats)
#, axis.title.y = element_blank()
, axis.title.x = element_text(size = my_ats)
#, axis.title.x = element_blank()
, axis.title.y = element_text(size = my_ats)
, axis.ticks.y = element_blank()
, plot.title = element_blank())+
labs(y = "Count"
, x = "Minor Allele Frequency"
)
g_af_hist_col
g_af_hist_col_med = g_af_hist_col +
geom_vline(data = df3_af_median, aes(xintercept = grp.median),linetype = "dashed")
g_af_hist_col_med
#=====================================================================
#---------------------------------
# AF: hist facet by mutation_class
#---------------------------------
g_af_mutinfo = ggplot(df3, aes(x = af
, fill = mutation_info_labels)) +
scale_fill_manual(values = c("#E69F00", "#999999")) +
geom_histogram() +
facet_grid(mutation_info_labels ~ ., scales = "free") +
#facet_wrap(mutation_info_labels ~ ., scales = "free") +
theme(axis.text.x = element_text(size = my_ats)
, axis.text.y = element_text(size = my_ats)
, axis.title.x = element_text(size = my_ats)
#, axis.title.y = element_blank()
, axis.title.y = element_text(size = my_ats)
, axis.ticks.y = element_blank()
#, plot.title = element_text(size = my_ats+5, face ="bold", hjust = 0.5)
, plot.title = element_blank()
#, strip.text = element_text(size = my_als)
, strip.text = element_blank()
, strip.background = element_blank()
, legend.text = element_text(size = my_als-4)
, legend.title = element_text(size = my_als-4)
, legend.position = c(0.8, 0.9)) +
labs(title = "Minor Allele Frequency (MAF)"
, x = "MAF"
, y = "Count"
, fill = "Mutation class")
g_af_mutinfo
g_af_mutinfo_med = g_af_mutinfo +
geom_vline(data = df3_af_median, aes(xintercept = grp.median),linetype = "dashed")
g_af_mutinfo_med
#=====================================================================
#------------------------
# AF: boxplot with stats
#------------------------
my_comparisons <- list( c("DM", "OM") )
g_af_bp = ggplot(df3, aes(x = mutation_info_labels
, y = af
, fill = mutation_info_labels))+
scale_fill_manual(values = c("#E69F00", "#999999")) +
geom_boxplot() +
theme(axis.text.x = element_text(size = my_ats)
, axis.text.y = element_text(size = my_ats)
, axis.title.x = element_text(size = my_ats)
#, axis.title.y = element_blank()
, axis.title.y = element_text(size = my_ats)
, axis.ticks.y = element_blank()
, plot.title = element_blank()
, strip.text = element_text(size = my_als)
, legend.text = element_text(size = my_als-4)
, legend.title = element_text(size = my_als-4)
, legend.position = "none") +
labs(y = "MAF"
, x = ""
, fill = "Mutation class")
g_af_bp_stats = g_af_bp + stat_compare_means(comparisons = my_comparisons
, method = "wilcox.test"
, paired = FALSE
#, label = "p.format"
, label = "p.signif")
g_af_bp_stats
######################################################################
# OR plots
######################################################################
#-----------
# OR: hist
#-----------
g_or_hist = ggplot(df3, aes(x = or_mychisq)) +
geom_histogram(colour = "white") +
theme(axis.text.x = element_text(size = my_ats)
, axis.text.y = element_text(size = my_ats)
#, axis.title.y = element_blank()
, axis.title.x = element_text(size = my_ats)
#, axis.title.x = element_blank()
, axis.title.y = element_text(size = my_ats)
, axis.ticks.y = element_blank()
, plot.title = element_blank())+
#, plot.title = element_text(size = my_ats+5, face ="bold", hjust = 0.5))+
labs(title = "Odds Ratio (OR)"
, x = "OR"
, y = "Count")
g_or_hist
#=====================================================================
#---------------------------------
# OR: hist facet by mutation_class
#---------------------------------
df3_or_median <- ddply(df3, "mutation_info_labels", summarise, grp.median = median(or_mychisq, na.rm = T))
head(df3_or_median)
g_or_mutinfo = ggplot(df3, aes(x = or_mychisq
, fill = mutation_info_labels)) +
scale_fill_manual(values = c("#E69F00", "#999999")) +
geom_histogram() +
facet_grid(mutation_info_labels ~ ., scales = "free") +
#facet_wrap(mutation_info_labels ~ ., scales = "free") +
scale_y_continuous(breaks = c(0, 15, 30, 45, 60, 75)) +
theme(axis.text.x = element_text(size = my_ats)
, axis.text.y = element_text(size = my_ats)
, axis.title.x = element_text(size = my_ats)
, axis.title.y = element_text(size = my_ats)
#, axis.title.y = element_blank()
, axis.ticks.y = element_blank()
#, plot.title = element_text(size = my_ats+5, face ="bold", hjust = 0.5)
, plot.title = element_blank()
#, strip.text = element_text(size = my_als)
, strip.text = element_blank()
, strip.background = element_blank()
, legend.text = element_text(size = my_als-4)
, legend.title = element_text(size = my_als-4)
, legend.position = c(0.8, 0.9))+
labs(title = "Odds Ratio (OR)"
, x = "OR"
, y = "Count"
, fill = "Mutation class")
g_or_mutinfo
g_or_mutinfo_med = g_or_mutinfo + geom_vline(data = df3_or_median, aes(xintercept = grp.median),
linetype = "dashed")
g_or_mutinfo_med
#=====================================================================
#------------------------
# OR: boxplot with stats
#------------------------
g_or_bp = ggplot(df3, aes(x = mutation_info_labels
, y = or_mychisq
, fill = mutation_info_labels))+
scale_fill_manual(values = c("#E69F00", "#999999")) +
geom_boxplot()+
theme(axis.text.x = element_text(size = my_ats)
, axis.text.y = element_text(size = my_ats)
, axis.title.x = element_text(size = my_ats)
#, axis.title.y = element_blank()
, axis.title.y = element_text(size = my_ats)
, axis.ticks.y = element_blank()
, plot.title = element_blank()
, strip.text = element_text(size = my_als)
, legend.text = element_text(size = my_als-4)
, legend.title = element_text(size = my_als-4)
, legend.position = "none") +
labs(y = "OR"
, x = ""
, fill = "Mutation class")
g_or_bp_stats = g_or_bp + stat_compare_means(comparisons = my_comparisons
, method = "wilcox.test"
, paired = FALSE
#, label = "p.format"
, label = "p.signif")
g_or_bp_stats
############################################################################
#==============================
# combine plots for outputs
#==============================
#-----------------------------------------
# combine the AF plots with overall title
#-----------------------------------------
p1_af = cowplot::plot_grid(g_af_hist
, g_af_mutinfo_med
#, g_af_mutinfo # without median line
, g_af_bp_stats
, nrow = 1
#, labels = c("(a)", "(b)", "(c)")
, labels = c("A", "B", "C")
, hjust = -1.5
, vjust = 0.2
, rel_widths = c(1.2/4, 2/4, 0.8/4)
, label_size = 18)
p1_af
title_af = ggdraw() + draw_label("Minor Allele Frequency (MAF)", fontface='bold', size = my_ats + 5)
p1_af_title = plot_grid(title_af, p1_af, ncol = 1, rel_heights = c(0.1, 1)) # rel_heights values control title margins
p1_af_title
#-----------------------------------------
# combine the OR plots with overall title
#-----------------------------------------
p2_or = cowplot::plot_grid(g_or_hist
, g_or_mutinfo_med
#, g_or_mutinfo # without median line
, g_or_bp_stats
, nrow = 1
#, labels = c("(d)", "(e)", "(f)")
, labels = c("D", "E", "F")
, hjust = -1.5
, vjust = 0.2
, rel_widths = c(1.2/4, 2/4, 0.8/4)
, label_size = 18)
p2_or
title_or = ggdraw() + draw_label("Odds Ratio (OR)", fontface = 'bold', size = my_ats + 5)
p2_or_title = plot_grid(title_or, p2_or, ncol = 1, rel_heights = c(0.1, 1)) # rel_heights values control title margins
p2_or_title
#----------------------------------------
# Plot 1: Combined AF and OR hist plots
# with median line on hist
#----------------------------------------
print(paste0("plot combined filename:", plot_af_or_combined_med))
svg(plot_af_or_combined_med, width = 15, height = 9)
p_combined_med = cowplot::plot_grid(p1_af_title, p2_or_title, nrow = 2)
p_combined_med
dev.off()
#----------------------------------------
# Plot 2: Combined AF and OR hist plots
# with median line on hist
#----------------------------------------
# uncomment the correct vars in p1_af and p2_or to generate this
#print(paste0("plot combined filename:", plot_af_or_combined))
#svg(plot_af_or_combined, width = 15, height = 9)
#p_combined = cowplot::plot_grid(p1_af_title, p2_or_title, nrow = 2)
#p_combined
#dev.off()
######################################################################