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.

1 | ```
rankCombine(DEscore, DSscore, DEscoreMat, DSscoreMat, DEweight = 0.5)
``` |

`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)). |

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

A list with two elements `geneScore`

and `genePermuteScore`

.

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

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.

1 2 3 4 5 6 7 | ```
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
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.