rankCombine: Integration of differential expression and differential...

In sunlightwang/SeqGSEA: Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing

Description

Integration of differential expression and differential splice scores with a rank-based strategy, which simultaneously integrates observed scores and permutation scores using the same ranks.

Usage

rankCombine(DEscore, DSscore, DEscoreMat, DSscoreMat, DEweight = 0.5)

Arguments

DEscore	differential expression scores, normalized.
DSscore	differential splice scores, normalized.
DEscoreMat	differential expression scores in permuted data sets, normalized.
DSscoreMat	differential splice scores in permuted data sets, normalized.
DEweight	any number between 0 and 1 (included), the weight of differential expression scores (so the weight for differential splice is (1-DEweight)).

Details

This integration method is also known as integration with global ranks. See Wang and Cairns (2013) for details.

Value

A list with two elements geneScore and genePermuteScore.

Author(s)

Xi Wang, [e-mail]

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

geneScore, genePermuteScore

Examples

data(DEscore, package="SeqGSEA")
data(DSscore, package="SeqGSEA")
data(DEscore.perm, package="SeqGSEA")
data(DSscore.perm, package="SeqGSEA")
combine <- rankCombine(DEscore, DSscore, DEscore.perm, DSscore.perm, DEweight=0.3) 
gene.score <- combine$geneScore
gene.score.perm <- combine$genePermuteScore

sunlightwang/SeqGSEA documentation built on Dec. 5, 2020, 5:52 p.m.