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edgeR (version 3.14.0)

plotExonUsage: Create a Plot of Exon Usage from Exon-Level Count Data

Description

Create a plot of exon usage for a given gene by plotting the (un)transformed counts for each exon, coloured by experimental group.

Usage

plotExonUsage(y, geneID, group=NULL, transform="none", counts.per.million=TRUE, legend.coords=NULL, ...)

Arguments

y
either a matrix of exon-level counts, a list containing a matrix of counts for each exon or a DGEList object with (at least) elements counts (table of counts summarized at the exon level) and samples (data frame containing information about experimental group, library size and normalization factor for the library size). Each row of y should represent one exon.
geneID
character string giving the name of the gene for which exon usage is to be plotted.
group
factor supplying the experimental group/condition to which each sample (column of y) belongs. If NULL (default) the function will try to extract if from y, which only works if y is a DGEList object.
transform
character, supplying the method of transformation to be applied to the exon counts, if any. Options are "none" (original counts are preserved), "sqrt" (square-root transformation) and "log2" (log2 transformation). Default is "none".
counts.per.million
logical, if TRUE then counts per million (as determined from total library sizes) will be plotted for each exon, if FALSE the raw read counts will be plotted. Using counts per million effectively normalizes for different read depth among the different samples, which can make the exon usage plots easier to interpret.
legend.coords
optional vector of length 2 giving the x- and y-coordinates of the legend on the plot. If NULL (default), the legend will be automatically placed near the top right corner of the plot.
...
optional further arguments to be passed on to plot.

Value

(invisibly) returns the transformed matrix of counts for the gene being plotted and produces a plot to the current device.

Details

This function produces a simple plot for comparing exon usage between different experimental conditions for a given gene.

See Also

spliceVariants for methods to detect genes with evidence for alternative exon usage.

Examples

Run this code
# generate exon counts from NB, create list object
y<-matrix(rnbinom(40,size=1,mu=10),nrow=10)
rownames(y) <- rep(c("gene.1","gene.2"), each=5)
d<-DGEList(counts=y,group=rep(1:2,each=2))
plotExonUsage(d, "gene.1")

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