GSEA.EnrichmentScore: Computes the enrichment score of a gene set

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

Description

'GSEA.EnrichmentScore' computes the weighted GSEA score of gene.set in gene.list

Usage

GSEA.EnrichmentScore(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. 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) arg.ES: Location in gene.list where the peak running enrichment occurs (peak of the 'mountain') RES: Numerical vector containing the running enrichment score for all locations in the gene list tag.indicator: Binary vector indicating the location of the gene sets (1's) in the gene list

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