runfGSEA: Run 2-sided fgseaMultilevel analysis (positive and negative)...

In cusom/CUSOM.ShinyHelpers: CU School of Medicine Helper Functions for Shiny Applications

Run 2-sided fgseaMultilevel analysis (positive and negative) with adjusted pvals

Description

Run 2-sided fgseaMultilevel analysis (positive and negative) with adjusted pvals

Usage

runfGSEA(geneset, ranks, minSize = 15, maxSize = 500, gseaParam = 0, eps = 0)

Arguments

geneset	list List of gene sets to check.
ranks	Named vector of gene-level stats (Gene + "Fold Change" or "rho"). Names should be the same as in 'pathways'
minSize	int default 15: Minimal size of a gene set to test. All pathways below the threshold are excluded.
maxSize	int default 500: Maximal size of a gene set to test. All pathways above the threshold are excluded.
gseaParam	int default 0: GSEA parameter value, all gene-level statis are raised to the power of 'gseaParam' before calculation of GSEA enrichment scores.
eps	numeric default 0.0: This parameter sets the boundary for calculating the p value.

Value

A tibble with GSEA results. Each row corresponds to a tested pathway. The columns are the following pathway: name of the pathway as in 'names(pathway)'; pval: an enrichment p-value; padj – a BH-adjusted p-value; log2err – the expected error for the standard deviation of the P-value logarithm. ES – enrichment score, same as in Broad GSEA implementation; NES – enrichment score normalized to mean enrichment of random samples of the same size; size – size of the pathway after removing genes not present in 'names(stats)'. leadingEdge – vector with indexes of leading edge genes that drive the enrichment, see http://software.broadinstitute.org/gsea/doc/GSEAUserGuideTEXT.htm#_Running_a_Leading.

cusom/CUSOM.ShinyHelpers documentation built on Oct. 23, 2023, 6:50 a.m.