Run DESeq for differential expression analysis

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Description

This function provides a wrapper to run DESeq for differential expression analysis. It includes two steps, DESeq::estimateSizeFactors and DESeq::estimateDispersions.

Usage

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runDESeq(geneCounts, label)

Arguments

geneCounts

a matrix containing read counts for each gene, can be the output of getGeneCount.

label

the sample classification labels.

Value

A CountDataSet object with size factors and dispersion parameters been estimated.

Author(s)

Xi Wang, xi.wang@newcastle.edu.au

References

Anders, S. and Huber, W. (2010) Differential expression analysis for sequence count data, Genome Biol, 11, R106.

See Also

getGeneCount, DENBTest, DENBStat4GSEA

Examples

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data(RCS_example, package="SeqGSEA")
geneCounts <- getGeneCount(RCS_example)
label <- label(RCS_example)
DEG <- runDESeq(geneCounts, label)

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