DESeq2: plotSparsity – R documentation

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plotSparsity

Sparsity plot

Description

A simple plot of the concentration of counts in a single sample over the sum of counts per gene. Not technically the same as "sparsity", but this plot is useful diagnostic for datasets which might not fit a negative binomial assumption: genes with many zeros and individual very large counts are difficult to model with the negative binomial distribution.

Usage

plotSparsity(x, normalized = TRUE, ...)

Arguments

`x`	a matrix or DESeqDataSet
`normalized`	whether to normalize the counts from a DESeqDataSEt
`...`	passed to `plot`

Examples

dds <- makeExampleDESeqDataSet(n=1000,m=4,dispMeanRel=function(x) .5)
dds <- estimateSizeFactors(dds)
plotSparsity(dds)

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