GSEA.EnrichmentScore2: Computes random permutation enrichment scores

In GSEA-MSigDB/GSEA_R: Gene Set Enrichment Analysis (GSEA)

Description

'GSEA.EnrichmentScore2' computes the weighted GSEA score of random permutations of a gene.set in gene.list

Usage

GSEA.EnrichmentScore2(gene.list, gene.set, weighted.score.type = 1,
  correl.vector = NULL)

Details

Internal 'GSEA' function. Computes the weighted GSEA score of gene.set in gene.list. It is the same calculation as in GSEA.EnrichmentScore but faster (x8) without producing the RES, arg.RES and tag.indicator outputs. This call is intended to be used to asses the enrichment of random permutations rather than the observed one. The weighted score type is the exponent of the correlation weight: 0 (unweighted = Kolmogorov-Smirnov), 1 (weighted), and 2 (over-weighted). When the score type is 1 or 2 it is necessary to input the correlation vector with the values in the same order as in the gene list. Inputs: gene.list: The ordered gene list (e.g. integers indicating the original position in the input dataset) gene.set: A gene set (e.g. integers indicating the location of those genes in the input dataset) weighted.score.type: Type of score: weight: 0 (unweighted = Kolmogorov-Smirnov), 1 (weighted), and 2 (over-weighted) correl.vector: A vector with the coorelations (e.g. signal to noise scores) corresponding to the genes in the gene list Outputs: ES: Enrichment score (real number between -1 and +1)

GSEA-MSigDB/GSEA_R documentation built on Nov. 30, 2021, 4:50 a.m.