GSEA_proc_R: Gene Set Enrichment Analysis (GSEA) with a new permutation...

In lusystemsbio/NetAct: NetAct -- a computational platform to construct core transcription factor regulatory networks using gene activity

Gene Set Enrichment Analysis (GSEA) with a new permutation method – implementation in R

Description

To improve computational efficiency, we devised a new permutation approach by swapping stats_vector. Here, the gene symbols/names are permutated without changing the ranking vector (stats_vector).

Usage

GSEA_proc_R(GSDB, DElist, minSize = 5, nperm = 1000)

Arguments

GSDB	gene set database (a list of gene sets, each of which is comprised of a vector genes)
DElist	a vector of DEG statistics for every gene in gene_list (rank_vector in the DEG results)
minSize	the minimum number of overlapping genes required for each gene set (a gene set filtering parameter, default: 5)
nperm	the number of gene list permutations (default: 1000)

Value

data.frame(rslt_mat): a table of GSEA results: tf: TF (gene set name). es: ES score. lens: number of overlapping genes in each gene set. pvals: p-value by counting. z: z-score. qvals: q-value from pvals.

lusystemsbio/NetAct documentation built on Sept. 7, 2024, 8:34 p.m.