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\title{Plot Biological Coefficient of Variation}
\name{plotBCV}
\alias{plotBCV}
\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", \dots)
}
\arguments{
\item{y}{a \code{DGEList} object.}
\item{xlab}{label for the x-axis.}
\item{ylab}{label for the y-axis.}
\item{pch}{the plotting symbol. See \code{\link{points}} for more details.}
\item{cex}{plot symbol expansion factor. See \code{\link{points}} for more details.}
\item{col.common}{color of line showing common dispersion}
\item{col.trend}{color of line showing dispersion trend}
\item{col.tagwise}{color of points showing genewise dispersions. Note that `tag' and `gene' are synonymous here.}
\item{\dots}{any other arguments are passed to \code{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{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)
}
\concept{Dispersion estimation}
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