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##################################################
##### integration of phQTL, mQTL, and eQTL #######
##################################################
# Set working directory and load libraries ####
remove(list = ls())
gc()
# load library
library(dplyr)
library(grid)
library(scales)
library(RColorBrewer)
library(devtools)
library(ggplot2)
# set directory
work.dir <- "C:/Users/harta005/Projects/seed-germination-qtl"
setwd(work.dir)
# gathering phQTL profile
phqtl.peak <- readRDS('qtl-peaks/peak_phqtl_without-outliers-not-transformed.RDS') %>%
mutate(qtl_level = 'phQTL') %>%
mutate(stage = 'phQTL')
# gathering mQTL profile
seed.stage <- c('pd', 'ar', 'im', 'rp')
mqtl.peak <- data.frame(matrix(nrow = 0, ncol = 12))
colnames(mqtl.peak) <- colnames(phqtl.peak)
for (i in seed.stage) {
table.tmp <- readRDS(paste0('qtl-peaks/peak_mqtl_', i, '-without-outliers-log-transformed.RDS')) %>%
mutate(qtl_level = 'mQTL', stage = i)
mqtl.peak <- rbind(mqtl.peak, table.tmp)
}
# gathering eQTL profiles
eqtl.peak <- data.frame(matrix(nrow = 0, ncol = 13))
colnames(eqtl.peak) <- colnames(phqtl.peak)
for (i in seed.stage) {
table.tmp <- readRDS(paste0('qtl-tables/table_single-stage-eqtl_', i, '.rds')) %>%
filter(qtl_type == 'trans') %>%
mutate(qtl_level = 'eQTL', stage = i) %>%
dplyr::select(colnames(phqtl.peak))
eqtl.peak <- rbind(eqtl.peak, table.tmp)
}
# creating the histogram plot ####
# plot style ####
presentation <- theme(axis.text.x = element_text(size=12, face="bold", color="black"),
axis.text.y = element_text(size=12, face="bold", color="black"),
axis.title.x = element_text(size=15, face="bold", color="black"),
axis.title.y = element_text(size=15, face="bold", color="black"),
strip.text.x = element_text(size=15, face="bold", color="black"),
strip.text.y = element_text(size=15, face="bold", color="black"),
plot.title = element_text(size=15, face="bold"),
panel.background = element_rect(fill = "white",color="black"),
panel.grid.major = element_line(colour = "grey80"),
panel.grid.minor = element_blank(),
legend.position = "right")
myColors <- brewer.pal(9,"Set1")[c(3,5,9,6,7)]
myColors <- c("black",brewer.pal(9,"Set1")[c(2,9)])
plot.colour <- c("#000000", "#E69F00", "#009E73", "#0072B2", "#D55E00")
names(plot.colour) <- c("cis", "DryFresh", "DryAR", "6H", "RP")
hist.colour <- c("#E69F00", "#009E73", "#0072B2", "#D55E00")
names(hist.colour) <- c("DryFresh", "DryAR", "6H", "RP")
names(myColors) <- c("cis","trans","none")
Snoekcols <- scale_colour_manual(name = "eQTL type",values = myColors)
Snoekfill <- scale_fill_manual(name = "eQTL type",values = myColors)
# plotting ####
overlap <- function(table, stage) {
for (i in 1:length(stage)) {
if (nrow(table) != 0) {
table <- subset(table, table[stage[i]] == T)
} else {
break
}
}
nrow(table)
}
all.peak <- rbind(phqtl.peak, mqtl.peak, eqtl.peak)
all.peak$stage <- factor(all.peak$stage, levels = c('phQTL', 'pd', 'ar', 'im', 'rp'))
qtl.hist <- ggplot(all.peak, aes(x=qtl_bp, fill = stage)) +
geom_histogram(binwidth = 2000000, right = T, origin = 0, alpha = 1) +
#geom_density(alpha = 0.5) +
facet_grid(factor(qtl_level, level = c('phQTL', 'mQTL', 'eQTL')) ~ qtl_chromosome, scales="free_y") +
presentation +
scale_fill_manual(values = c('#964B00', '#ccbb44', '#228833', '#4477aa', '#cc3311')) +
theme(legend.position = "top", legend.text=element_text(size=5)) +
labs(x="QTL peak position (Mb)",y="QTL counts") +
scale_x_continuous(breaks=c(5, 10, 15, 20, 25, 30, 35, 40)*10^6,labels=c(5, 10, 15, 20, 25, 30, 35, 40))
tiff(file = paste0("figures/all-qtl-hist.tiff"),
width = 2250,
height = 1600,
units = 'px',
res = 300,
compression = 'lzw')
qtl.hist
dev.off()
# venn diagram ####
qtl.table.summary <- data.frame(matrix(ncol = 18, nrow = 0))
window.nu <- 2e6
maxsize <- 100e6
chr.num <- 5
all.peak2 <- all.peak %>%
mutate(interval = findInterval(qtl_bp, seq(1, maxsize, by = window.nu))) %>%
select(trait, qtl_chromosome, interval, qtl_significance, stage, qtl_level) %>%
#group_by(trait, qtl_chromosome, interval, qtl_significance, stage, qtl_level) %>%
count(qtl_chromosome, interval, qtl_level) %>%
#ungroup() %>%
spread(qtl_level, n) %>%
#select(phQTL, mQTL, eQTL) %>%
replace(is.na(.), 0)
overlap <- function(table, stage) {
for (i in 1:length(stage)) {
if (nrow(table) != 0) {
table <- subset(table, table[stage[i]] > 0)
} else {
break
}
}
nrow(table)
}
overlap(all.peak2, c('eQTL', 'phQTL', 'mQTL'))
draw.triple.venn(area1 = overlap(all.peak2, 'phQTL'),
area3 = overlap(all.peak2, 'mQTL'),
area2 = overlap(all.peak2, 'eQTL'),
n13 = overlap(all.peak2, c('phQTL', 'mQTL')),
n12 = overlap(all.peak2, c('phQTL', 'eQTL')),
n23 = overlap(all.peak2, c('mQTL', 'eQTL')),
n123 = overlap(all.peak2, c('phQTL', 'mQTL', 'eQTL')),
category = c('phQTL', 'eQTL', 'mQTL'),
lty = 'blank',
fill = c('#0d98ba', '#c71585', '#f8d568'))
#alpha = 0.9)