plotSA {limma} | R Documentation

## 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

`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.

[Package limma version 2.18.3 Index]