Main function of gene set enrichment analysis

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Description

The main function of gene set enrichment analysis

Usage

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GSEnrichAnalyze(gene.set, gene.score, gene.score.perm, weighted.type = 1)

Arguments

gene.set

a SeqGeneSet object.

gene.score

a vector of integrated gene scores in the same order as genes listed in the geneList slot of gene.set.

gene.score.perm

a matrix of integrated gene scores on permutation data sets; row: genes; col: permutation.

weighted.type

weight type for gene scores; default: 1.

Value

A SeqGeneSet object with many slots updated, such as GSEA.ES and GSEA.pval.

Author(s)

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

References

Xi Wang and Murray J. Cairns (2013). Gene Set Enrichment Analysis of RNA-Seq Data: Integrating Differential Expression and Splicing. BMC Bioinformatics, 14(Suppl 5):S16.

See Also

normES, signifES

Examples

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data(DEscore, package="SeqGSEA")
data(DSscore, package="SeqGSEA")
gene.score <- geneScore(DEscore, DSscore, method="linear", DEweight = 0.3)
data(DEscore.perm, package="SeqGSEA")
data(DSscore.perm, package="SeqGSEA")
gene.score.perm <- genePermuteScore(DEscore.perm, DSscore.perm, method="linear",  DEweight=0.3)
data(GS_example, package="SeqGSEA") 
GS_example <- GSEnrichAnalyze(GS_example, gene.score, gene.score.perm)
topGeneSets(GS_example, 5)

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