genePermuteScore {SeqGSEA} | R Documentation |
Calculate gene scores on permutation data sets
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.
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)