Plot Genome Coverage Graphs using grid package in R

It is a common task to visualize the genome coverages across different conditions. This usually requires a multiple panel graph with some shared axis labels and a title shared by all the panels. One easy way to do this is using the grid packages in R. The code below shows how to do it.

setwd(‘../results’)
coverages <- read.csv(‘Ambion_coverage_small.csv’, header=TRUE, sep=’,’)

library(ggplot2)

## 26 Ambion
title = expression(paste(“26”, degree, “C rep 1”))
p23 <- ggplot(coverages, aes(x=position, y=NBA.23)) + geom_line()
p23 <- p23 + theme(axis.title.x = element_blank(),
axis.title.y = element_blank())
p23 <- p23 + ggtitle(title)

title = expression(paste(“26”, degree, “C rep 2”))
p25 <- ggplot(coverages, aes(x=position, y=NBA.25)) + geom_line()
p25 <- p25 + theme(axis.title.x = element_blank(),
axis.title.y = element_blank())
p25 <- p25 + ggtitle(title)

title = expression(paste(“37”, degree, “C rep 1”))
p20 <- ggplot(coverages, aes(x=position, y=NBA.20)) + geom_line()
p20 <- p20 + theme(axis.title.x = element_blank(),
axis.title.y = element_blank())
p20 <- p20 + ggtitle(title)

title = expression(paste(“37”, degree, “C rep 2”))
p21 <- ggplot(coverages, aes(x=position, y=NBA.21)) + geom_line()
p21 <- p21 + theme(axis.title.x = element_blank(),
axis.title.y = element_blank())
p21 <- p21 + ggtitle(title)

title = expression(paste(“37”, degree, “C rep 3”))
p22 <- ggplot(coverages, aes(x=position, y=NBA.22)) + geom_line()
p22 <- p22 + theme(axis.title.x = element_blank(),
axis.title.y = element_blank())
p22 <- p22 + ggtitle(title)

library(grid)
pdf(‘Ambion_genome_coverage.pdf’)
grid.newpage()

pushViewport(viewport(layout=grid.layout(6,2, heights= unit(c(0.8, 5, 5, 5, 5, 5), ‘null’), widths=unit(c(0.5, 5), ‘null’))))

grid.text(“Genome Coverages of Ambion Libraries”, vp = viewport(layout.pos.row = 1)) # a title for the entire grid

grid.text(“Row read counts”, rot=90, vp = viewport(layout.pos.col = 1)) # a title for the entire grid
print(p23, vp = viewport(layout.pos.row=2, layout.pos.col=2))
print(p25, vp = viewport(layout.pos.row=3, layout.pos.col=2))
print(p20, vp = viewport(layout.pos.row=4, layout.pos.col=2))
print(p21, vp = viewport(layout.pos.row=5, layout.pos.col=2))
print(p22, vp = viewport(layout.pos.row=6, layout.pos.col=2))
dev.off()

The above code uses a grid of 6 rows and 2 columns. The first column and the first row are used for shared y-axis and a title for the entire grid. The rest 5 rows in 1 column are used to plot all the panels. There are also some tricks for hide x- and y-axis labels for every panel, and a way to print the degree sign along with other text as panel titles.

These code generate the following figure.

Ambion_genome_coverage_small

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