rankCombine {SeqGSEA} | R Documentation

## Integration of differential expression and differential splice scores with a rank-based strategy

### 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, 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

`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

[Package SeqGSEA version 1.34.0 Index]