independentFiltering: Perform independent filtering in differential expression...

In drisso/zinbwave: Zero-Inflated Negative Binomial Model for RNA-Seq Data

Perform independent filtering in differential expression analysis.

Description

This function uses the DESeq2 independent filtering method to increase detection power in high throughput gene expression studies.

Usage

independentFiltering(object, filter, objectType = c("edgeR", "limma"))

Arguments

object	Either a DGELRT-class object or a data.frame with differential expression results.
filter	The characteristic to use for filtering, usually a measure of normalized mean expression for the features.
objectType	Either "edgeR" or "limma". If "edgeR", it is assumed that object is of class DGELRT-class, the output of glmLRT. If "limma", it is assumed that object is a data.frame and the output of a limma-voom analysis.

Author(s)

Koen Van den Berge

References

Michael I Love, Wolfgang Huber, and Simon Anders. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12):550, dec 2014.

See Also

results

drisso/zinbwave documentation built on March 18, 2024, 5:13 p.m.