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Run simple fGSEA enrichment

simple_fgsea.Rd

simple_fgsea calls a simple fGSEA from the fgsea package

Usage

simple_fgsea(
  pathways,
  stats,
  minSize = 1,
  maxSize = length(stats) - 1,
  eps = 1e-50,
  scoreType = c("std", "pos", "neg"),
  nPermSimple = 1000
)

Arguments

pathways

List of metabolite sets to check.

stats

Named vector of metabolite-level stats. Names should be the same as in 'pathways'

minSize

Minimal size of a metabolite set to test. All pathways below the threshold are excluded.

maxSize

Maximal size of a metabolite set to test. All pathways above the threshold are excluded.

eps

This parameter sets the boundary for calculating the p value.

scoreType

This parameter defines the GSEA score type. Possible options are ("std", "pos", "neg")

nPermSimple

Number of permutations in the simple fgsea implementation for preliminary estimation of P-values

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; \item size -- size of the pathway after removing genes not present innames(stats)`.

  • leadingEdge – vector with indexes of leading edge genes that drive the enrichment, see https://www.gsea-msigdb.org/gsea/doc/GSEAUserGuideTEXT.htm#_Running_a_Leading.

Examples

bg = list("Term_A" = paste0("mol_", sample(100,20)),"Term_B" = paste0("mol_", sample(100,20)))
mol_ranks = runif(10, -3, 3)
names(mol_ranks) = sample(unique(unlist(bg)), 10)
mol_ranks = mol_ranks[order(mol_ranks)]
simple_fgsea(pathways = bg, stats = mol_ranks, minSize = 3, scoreType = "std")
#>    pathway      pval      padj         ES       NES nMoreExtreme  size
#>     <char>     <num>     <num>      <num>     <num>        <num> <int>
#> 1:  Term_A 0.1056338 0.1108696  0.8000000  1.489072           59     5
#> 2:  Term_B 0.1108696 0.1108696 -0.7664702 -1.452191           50     5
#>     leadingEdge
#>          <list>
#> 1: mol_45, ....
#> 2: mol_53, ....