# plotSA: Sigma vs A plot for microarray linear model

## 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

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`

.

## See Also

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