vst {EnrichmentBrowser} | R Documentation |
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.
vst(se)
se |
An object of class |
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).
An object of class SummarizedExperiment
.
Ludwig Geistlinger <Ludwig.Geistlinger@sph.cuny.edu>
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.
cpm
and estimateDisp
se <- makeExampleData(what="SE", type="rseq") vstSE <- vst(se)