fgseaSimpleImpl {fgsea} | R Documentation

## Runs preranked gene set enrichment analysis for preprocessed input data.

### Description

Runs preranked gene set enrichment analysis for preprocessed input data.

### Usage

    fgseaSimpleImpl(pathwayScores, pathwaysSizes, pathwaysFiltered,
      leadingEdges, permPerProc, seeds, toKeepLength, stats, BPPARAM)

### Arguments

`pathwayScores` | Vector with enrichment scores for the 'pathways'.
`pathwaysSizes` | Vector of path sizes.
`pathwaysFiltered` | Filtered pathways.
`leadingEdges` | Leading edge genes.
`permPerProc` | Parallelization parameter for permutations.
`seeds` | Seed vector
`toKeepLength` | Number of 'pathways' that meet the condition for 'minSize' and 'maxSize'.
`stats` | Named vector of gene-level stats. Names should be the same as in 'pathways'
`BPPARAM` | Parallelization parameter used in bplapply. Can be used to specify cluster to run. If not initialized explicitly or by setting 'nproc' default value 'bpparam()' is used.

### Value

A table 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;

- ES – enrichment score, same as in Broad GSEA implementation;

- NES – enrichment score normalized to mean enrichment of random samples of the same size;

- nMoreExtreme' – a number of times a random gene set had a more extreme enrichment score value;

- 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.

[Package fgsea version 1.10.1 Index]