R: Sigma vs A plot for microarray linear model

plotSA {limma}

R Documentation

Sigma vs A plot for microarray linear model

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

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

`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`

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.

A plot is created on the current graphics device.

Gordon Smyth