plotBCV: Plot Biological Coefficient of Variation

In edgeR: Empirical Analysis of Digital Gene Expression Data in R

Description

Plot the genewise biological coefficient of variation (BCV) against gene abundance (in log2 counts per million).

Usage

plotBCV(y, xlab="Average log CPM", ylab="Biological coefficient of variation",
     pch=16, cex=0.2, col.common="red", col.trend="blue", col.tagwise="black", ...)

Arguments

y	a DGEList object.
xlab	label for the x-axis.
ylab	label for the y-axis.
pch	the plotting symbol. See points for more details.
cex	plot symbol expansion factor. See points for more details.
col.common	color of line showing common dispersion
col.trend	color of line showing dispersion trend
col.tagwise	color of points showing genewise dispersions. Note that ‘tag’ and ‘gene’ are synonymous here.
...	any other arguments are passed to plot.

Details

The BCV is the square root of the negative binomial dispersion. This function displays the common, trended and genewise BCV estimates.

Value

A plot is created on the current graphics device.

Author(s)

Davis McCarthy, Yunshun Chen, Gordon Smyth

Examples

BCV.true <- 0.1
y <- DGEList(matrix(rnbinom(6000, size = 1/BCV.true^2, mu = 10),1000,6))
y <- estimateCommonDisp(y)
y <- estimateTrendedDisp(y)
y <- estimateTagwiseDisp(y)
plotBCV(y)

Example output

Loading required package: limma

edgeR documentation built on Jan. 16, 2021, 2:03 a.m.