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Ploting_functions.R
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Ploting_functions.R
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#########
# Author: Martin Machyna
# Date: 08/09/21
# Description: Functions for creating sequencing tracks plots and gene annotated barplots in R
#########
plot_tl <- function(dir, name, chr, start, end, yscale = NULL, labx = TRUE) {
# dir - directory to serch for bigWig files
# name - a unique portion of the file names that selects all mutation track files for both strands e.g. "NMD_rep1"
# chr - chromosome identifier for plotting window
# start - start (leftmost) position for plotting window <int>
# end - end (rightmost) position for plotting window <int>
# yscale - optional: vector in format c(min,max) for y axis scale (default: autoscale)
# labx - optional: show genomic coordinates on x axis (default: TRUE)
#
# chr, start, end can also be supplied as vectors of the same length
# Requires: tidyverse, rtracklayer, cowplot, GenomicRanges
# load packages
library(tidyverse)
library(rtracklayer)
library(cowplot)
library(GenomicRanges)
# Get paths to all .bigWig files
bwFiles <- dir(dir, pattern = paste0(".*", name, ".*bigWig"), full.names = TRUE)
if(length(bwFiles) == 0) {stop("No files found at provided path")}
# Create region that will be plotted
selectRange <- GRanges(seqnames = chr, ranges = IRanges(start = start, end = end))
# Load data from .bigWig files
bwTracks <- NULL
for (f in bwFiles) {
n <- basename(f) %>% str_extract('[0-5].(pos|min)')
bwTracks[[n]] <- import(f, which = selectRange) %>% as.data.frame()
}
bwTracks <- bind_rows(bwTracks, .id = "id") %>% # combine tracks together and mark them with name
mutate(id = str_extract(id, '[0-5]')) %>% # extract number of mutations from name
mutate(start = start - 1) %>% # adjust start becuase it is 1-based
mutate(score_m = if_else(score < 0, score, 0), # split minus and plus score
score = if_else(score >= 0, score, 0))
if(nrow(bwTracks) == 0) {stop("No data retrieved from .bigWig files")}
tlPlot <- bwTracks %>%
mutate(id = factor(id, levels = c(0:5))) %>% # assign factors to mutation counts in order to preserve color scale
ggplot() +
ggplot2::geom_rect(aes(xmin = start, xmax = end, ymin = score_m, ymax = score, fill = id)) +
scale_fill_manual(values = c("#c8c8c8", "#fa9696", "#fa0000", "#960000", "#640000", "#320000"),
name = "Muts",
limits = as.character(0:5) ) +
geom_hline(yintercept = 0, color = "grey80", size = 0.3)+
theme_half_open() +
theme(axis.line.x = element_blank(),
axis.title.y = element_text(angle = 0, vjust = 0.5, hjust = 1) )
if (!labx) {
tlPlot <- tlPlot +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())
}
if (!is.null(yscale)){
if (is.na(yscale[1])) {yscale[1] <- ceiling(min(bwTracks$score_m))}
if (is.na(yscale[2])) {yscale[2] <- floor(max(bwTracks$score))}
tlPlot <- tlPlot +
coord_cartesian(ylim = c(yscale[1], yscale[2])) +
scale_y_continuous(breaks = c(yscale[1], yscale[2]), expand = c(0,0))
} else {
tlPlot <- tlPlot +
scale_y_continuous(breaks = c(ceiling(min(bwTracks$score_m)), floor(max(bwTracks$score))), expand = c(0,0))
}
tlPlot
}
plot_track <- function(dir, name, chr, start, end, yscale = NULL, labx = TRUE, snames = name) {
# dir - directory to serch for bigWig files
# name - either single or vector of names to distinguish files e.g. "NMD_rep1"
# chr - chromosome identifier for plotting window
# start - start (leftmost) position for plotting window <int>
# end - end (rightmost) position for plotting window <int>
# yscale - optional: vector in format c(min,max) for y axis scale (default: autoscale)
# labx - optional: show genomic coordinates on x axis (default: TRUE)
# snames - optional: sample names for leged (default: file name)
#
# chr, start, end can also be supplied as vectors of the same length
# Requires: tidyverse, rtracklayer, cowplot, GenomicRanges
# load packages
library(tidyverse)
library(rtracklayer)
library(cowplot)
library(GenomicRanges)
# Get paths to all .bigWig files
bwFiles <- NULL
for (n in name) {
bwFiles <- c(bwFiles, dir(dir, pattern = paste0(".*", n, ".*bigWig"), full.names = TRUE))
}
if(length(bwFiles) == 0) {stop("No files found at provided path")}
# Create region that will be plotted
selectRange <- GRanges(seqnames = chr, ranges = IRanges(start = start, end = end))
bwTracks <- NULL
# Load data from .bigWig files
for (f in bwFiles) {
n <- name[f == bwFiles]
bwTracks[[n]] <- import(f, which = selectRange) %>% as.data.frame()
}
bwTracks <- bind_rows(bwTracks, .id = "id") %>% # combine tracks together and mark them with name
mutate(start = start - 1) %>% # adjust start becuase it is 1-based
mutate(score_m = if_else(score < 0, score, 0), # split minus and plus score
score = if_else(score >= 0, score, 0)) %>%
mutate(id = factor(id)) # assign factors to file data
if(nrow(bwTracks) == 0) {stop("No data retrieved from .bigWig files")}
tlPlot <- bwTracks %>%
ggplot() +
ggplot2::geom_rect(aes(xmin = start, xmax = end, ymin = score_m, ymax = score, fill = id)) +
scale_fill_grey(labels = snames,
limits = levels(bwTracks$id)) +
geom_hline(yintercept = 0, color = "grey80", size = 0.3)+
theme_half_open() +
theme(axis.line.x = element_blank(),
axis.title.y = element_text(angle = 0, vjust = 0.5, hjust = 1),
legend.title = element_blank())
if (length(name) == 1) { tlPlot <- tlPlot + theme(legend.position = "none") }
if (labx) {
tlPlot <- tlPlot +
xlab(bwTracks$seqnames[1])
}
else {
tlPlot <- tlPlot +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())
}
if (!is.null(yscale)){
if (is.na(yscale[1])) {yscale[1] <- ceiling(min(bwTracks$score_m))}
if (is.na(yscale[2])) {yscale[2] <- floor(max(bwTracks$score))}
tlPlot <- tlPlot +
coord_cartesian(ylim = c(yscale[1], yscale[2])) +
scale_y_continuous(breaks = c(yscale[1], yscale[2]), expand = c(0,0))
} else {
tlPlot <- tlPlot +
scale_y_continuous(breaks = c(ceiling(min(bwTracks$score_m)), floor(max(bwTracks$score))), expand = c(0,0))
}
tlPlot
}
plot_BarGene <- function(name_of_gene, annotation, bar_ylab = "", labx = TRUE) {
require(tidyverse)
require(ggbio)
require(rtracklayer)
require(GenomicRanges)
require(cowplot)
require(patchwork)
# name_of_gene - name of gene for plotting, has to match gene_name column values in annotation
# bar_ylab - y axis label for barplot (default: off)
# labx - show genomic coordinates on x axis (default: TRUE)
# annotation - data.frame used for plotting
# input is dataframe of exon data from ideally 1 but possibly multiple transcripts
# annotation data.frame has to contain these columns: seqnames, start, end, strand, score, sd, transcript_id, gene_name
# each row has information about a single exon: seqnames - chromosome name
# start - leftmost edge of exon
# end - rightmost edge of exon
# strand - strand information
# score - value for barplot
# sd - value for error bars
# transcript_id - transcript identifier this exon belongs to
# gene_nname - name of gene this exon belongs to
# Requires: tidyverse, rtracklayer, ggbio, cowplot, GenomicRanges, patchwork
annotation_GR <- annotation %>%
filter(gene_name == name_of_gene) %>%
makeGRangesFromDataFrame(keep.extra.columns = TRUE)
gene_width <- max(annotation$end) - min(annotation$start)
bar_width <- gene_width / nrow(annotation) # range diveded by number of exonic parts
annotation <- annotation %>%
arrange(start) %>%
mutate(bar_start = min(annotation$start) + (bar_width * 1:nrow(annotation)) ) %>%
mutate(score_m = if_else(score < 0, score, 0), # split minus and plus score
score_p = if_else(score >= 0, score, 0))
yscale <- ceiling(max(abs(annotation$score)))
xlim_min <- min(annotation$start) - gene_width * 0.005
xlim_max <- max(annotation$end) + gene_width * 0.005
p1 <- annotation %>%
ggplot() +
ggplot2::geom_rect(aes(xmin = bar_start, xmax = bar_start - bar_width * 0.8, ymin = score_m, ymax = score_p)) +
geom_errorbar(aes(x = bar_start - bar_width * 0.4, y = score, ymax = score + sd, ymin = score - sd),
width = bar_width * 0.2) +
theme_half_open() +
background_grid(major = "y",
color.major = "grey80") +
theme(axis.text.x = element_blank(),
axis.title.x = element_blank(),
axis.ticks.x = element_blank(),
axis.line.x = element_blank()) +
coord_cartesian(ylim = c(-yscale, yscale),
xlim = c( xlim_min, xlim_max)) +
labs(title = name_of_gene,
subtitle = paste0(annotation$seqnames[1], ": ", min(annotation$start), "-", max(annotation$end)),
y = bar_ylab)
p2 <- data.frame( x = annotation$bar_start - bar_width * 0.4, y = rep(1, nrow(annotation)), exon = 1:nrow(annotation)) %>%
add_row(x = (annotation$start + annotation$end) / 2, y = rep(0, nrow(annotation)), exon = 1:nrow(annotation)) %>%
ggplot() +
geom_line(aes(x = x, y = y, group = exon)) +
coord_cartesian(xlim = c(xlim_min, xlim_max)) +
theme_void()
p3 <- annotation_GR %>% ggplot() +
geom_alignment(aes(group = transcript_id), group.selfish = TRUE) +
theme_half_open() +
background_grid(major = "y",
color.major = "grey80") +
theme(axis.line.x = element_blank()) +
coord_cartesian(xlim = c(xlim_min, xlim_max))
labs(title = name_of_gene)
if (!labx) {
p3 <- p3 +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())
}
# patchwork lib
wrap_plots(p1 + p2 + p3@ggplot +
plot_layout(ncol = 1, heights = c(2, 1, 1), guides = 'collect'))
}
plot_tl("TracksBigwig/Control/", "1hr_1", "chr6", 36592363, 36607600)
plot_track("TracksBigwig/Control", c("1hr_1.TC.0.pos", "1hr_1.TC.1.pos"), "chr6", 36592363, 36607600)
plot_BarGene("SRSF3", annot, bar_ylab = "Data +/- SD")
# Plots stacking with patchwork
p1 <- plot_BarGene("SRSF3", annot, bar_ylab = "Data +/- SD", labx = FALSE)
p2 <- plot_track("TracksBigwig/Control", c("1hr_1.TC.0.pos", "1hr_1.TC.1.pos"), "chr6", 36593781, 36606397, labx = FALSE, snames = c("Sample1", "Sample2"))
p3 <- plot_tl("TracksBigwig/Control/", "1hr_1", "chr6", 36593781, 36606397) + ylab("Sample")
p1 + p2 + p3 + plot_layout(ncol = 1, heights = c(4, 1, 1), guides = 'collect')