GSEA_permut_R_revised: Compute ES scores for Gene Set Enrichment Analysis (GSEA)...

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

Compute ES scores for Gene Set Enrichment Analysis (GSEA) with a new permutation method (using a revised algorithm)

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). This function becomes unused in NetAct, as a much faster c++ implementation (GSEA_permute) is provided.

Usage

GSEA_permut_R_revised(sim_all, gene_set, stats_vector, N)

Arguments

sim_all	a vector of genes in the expression data
gene_set	a vector of genes in the gene set
stats_vector	a vector of DEG statistics for every gene in gene_list (rank_vector in the DEG results); Absolute values of the t-statistics are required for the desired performance.
N	total number of genes (size of sim_all)

Value

ES: enrichment score

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