DESeq2: plotMA – R documentation

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plotMA

MA-plot from base means and log fold changes

Description

A simple helper function that makes a so-called "MA-plot", i.e. a scatter plot of log2 fold changes (on the y-axis) versus the mean of normalized counts (on the x-axis).

Usage

## S4 method for signature 'DESeqDataSet'
plotMA(
  object,
  alpha = 0.1,
  main = "",
  xlab = "mean of normalized counts",
  ylim,
  colNonSig = "gray60",
  colSig = "blue",
  colLine = "grey40",
  returnData = FALSE,
  MLE = FALSE,
  ...
)

## S4 method for signature 'DESeqResults'
plotMA(
  object,
  alpha,
  main = "",
  xlab = "mean of normalized counts",
  ylim,
  colNonSig = "gray60",
  colSig = "blue",
  colLine = "grey40",
  returnData = FALSE,
  MLE = FALSE,
  ...
)

Arguments

`object`	a `DESeqResults` object produced by `results`; or a `DESeqDataSet` processed by `DESeq`, or the individual functions `nbinomWaldTest` or `nbinomLRT`
`alpha`	the significance level for thresholding adjusted p-values
`main`	optional title for the plot
`xlab`	optional defaults to "mean of normalized counts"
`ylim`	optional y limits
`colNonSig`	color to use for non-significant data points
`colSig`	color to use for significant data points
`colLine`	color to use for the horizontal (y=0) line
`returnData`	logical, whether to return the data.frame used for plotting
`MLE`	if `betaPrior=TRUE` was used, whether to plot the MLE (unshrunken estimates), defaults to FALSE. Requires that `results` was run with `addMLE=TRUE`. Note that the MLE will be plotted regardless of this argument, if DESeq() was run with `betaPrior=FALSE`. See `lfcShrink` for examples on how to plot shrunken log2 fold changes.
`...`	further arguments passed to `plotMA` if object is `DESeqResults` or to `results` if object is `DESeqDataSet`

Details

This function is essentially two lines of code: building a data.frame and passing this to the plotMA method for data.frame from the geneplotter package. The code was modified in version 1.28 to change from red to blue points for better visibility for users with color-blindness. The original plots can still be made via the use of returnData=TRUE and passing the resulting data.frame directly to geneplotter::plotMA. The code of this function can be seen with: getMethod("plotMA","DESeqDataSet") If the object contains a column svalue then these will be used for coloring the points (with a default alpha=0.005).

Author(s)

Michael Love

Examples

dds <- makeExampleDESeqDataSet()
dds <- DESeq(dds)
plotMA(dds)
res <- results(dds)
plotMA(res)

DESeq2

Differential gene expression analysis based on the negative binomial distribution

v1.30.1

LGPL (>= 3)

Authors

Michael Love [aut, cre], Constantin Ahlmann-Eltze [ctb], Kwame Forbes [ctb], Simon Anders [aut, ctb], Wolfgang Huber [aut, ctb]

Initial release