Description Usage Arguments Details Value Author(s) See Also

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

1 2 |

`fit` |
an |

`xlab` |
label for x-axis |

`ylab` |
label for y-axis |

`zero.weights` |
logical, should genes with all zero weights be plotted? |

`pch` |
vector of codes for plotting characters. |

`cex` |
numeric, vector of expansion factors for plotting characters. |

`col` |
plotting colors for regular and outlier variances respectively. |

`...` |
any other arguments are passed to |

This plot is used to check the mean-variance relationship of the expression data, after fitting a linear model.
A scatterplot of residual-variances vs average log-expression is created.
The plot is especially useful for examining the mean-variance trend estimated by `eBayes`

or `treat`

with `trend=TRUE`

.
It can be considered as a routine diagnostic plot in the limma-trend pipeline.

If robust empirical Bayes was used to create `fit`

, then outlier variances are highlighted in the color given by `col[2]`

.

The y-axis is square-root `fit$sigma`

, where `sigma`

is the estimated residual standard deviation.
The y-axis therefore corresponds to quarter-root variances.
The y-axis was changed from log2-variance to quarter-root variance in limma version 3.31.21.
The quarter-root scale matches the similar plot produced by the `voom`

function and gives a better plot when some of the variances are close to zero.

See `points`

for possible values for `pch`

and `cex`

.

A plot is created on the current graphics device.

Gordon Smyth

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

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