plotSA: Sigma vs A plot for microarray linear model

In richierocks/limma2: Linear Models for Microarray Data

Description

Plot log residual standard deviation versus average log expression for a fitted microarray linear model.

Usage

plotSA(fit, xlab="Average log-expression", ylab="log2(sigma)", zero.weights=FALSE, pch=16, cex=0.2, ...)

Arguments

fit	an MArrayLM object.
xlab	character string giving label for x-axis
ylab	character string giving label for y-axis
pch	vector or list of plotting characters. Default is integer code 16 which gives a solid circle.
cex	numeric expansion factor for plotting character. Defaults to 0.2.
zero.weights	logical, should spots with zero or negative weights be plotted?
...	any other arguments are passed to plot

Details

This plot is used to check the mean-variance relationship of the expression data, after fitting a linear model.

See points for possible values for pch and cex.

Value

A plot is created on the current graphics device.

Author(s)

Gordon Smyth

See Also

An overview of diagnostic functions available in LIMMA is given in 09.Diagnostics.

richierocks/limma2 documentation built on May 27, 2019, 8:47 a.m.