Description Usage Arguments Details Value Author(s) References See Also Examples

Calculate gene scores on permutation data sets

1 2 | ```
genePermuteScore(DEscoreMat, DSscoreMat = NULL, method = c("linear", "quadratic", "rank"),
DEweight = 0.5)
``` |

`DEscoreMat` |
normalized DE scores on permutation data sets. |

`DSscoreMat` |
normalized DS scores on permutation data sets. |

`method` |
one of the integration methods: linear, quadratic, or rank; default: linear. |

`DEweight` |
any number between 0 and 1 (included), the weight of differential expression scores (the weight for differential splice is (1-DEweight)). |

The integration methods including "linear", "quadratic", and "rank" are detailed in Wang and Cairns (2013). Here the rank method refers only to the method using data-set-specific ranks.

For DE-only analysis, just specify DEweight to be 1, and the DSscoreMat value can be NULL.

A gene score matrix.

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 | ```
data(DEscore.perm, package="SeqGSEA")
data(DSscore.perm, package="SeqGSEA")
# linear combination with weight for DE 0.3
gene.score.perm <- genePermuteScore(DEscore.perm, DSscore.perm, method="linear", DEweight=0.3)
# DE only analysis
gene.score.perm <- genePermuteScore(DEscore.perm, DEweight=1)
``` |

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