vst {EnrichmentBrowser} | R Documentation

## Variance-stabilizing transformation for RNA-seq expression data

### Description

This function implements a variance-stabilizing transformation (VST) for RNA-seq read count data. It accounts for differences in sequencing depth between samples and over-dispersion of read count data. Permutation-based enrichment methods can then be applied as for microarray data.

### Usage

    vst(se)

### Arguments

`se` | An object of class `SummarizedExperiment`.

### Details

The VST uses the cpm function implemented in the edgeR package to compute moderated log2 read counts. Using edgeR's estimate of the common dispersion phi, the prior.count parameter of the cpm function is chosen as 0.5 / phi as previously suggested (Harrison, 2015).

### Value

An object of class `SummarizedExperiment`.

### Author(s)

Ludwig Geistlinger <Ludwig.Geistlinger@sph.cuny.edu>

### References

Harrison (2015) Anscombe's 1948 variance stabilizing transformation for the negative binomial distribution is well suited to RNA-seq expression data. doi:10.7490/f1000research.1110757.1

Anscombe (1948) The transformation of Poisson, binomial and negative-binomial data. Biometrika 35(3-4):246-54.

Law et al. (2014) voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15:29.

### See Also

`cpm` and `estimateDisp`

### Examples

        se <- makeExampleData(what="SE", type="rseq")
        vstSE <- vst(se)

[Package EnrichmentBrowser version 2.14.3 Index]