Gene set enrichment (GSE) based on a hypergeometric test.

Takes a set of target genes, a list of gene sets and calculates a p-value (hypergeometric test) and odds ratio (OR) against all the gene sets. Also applies a multiple hypothesis correction (BH) to the p-values.

Usage

gse_hypergeometric(
  target_genes,
  gene_set_list,
  gene_universe = NULL,
  threshold = 0.05,
  minimum_overlap = 3L,
  .verbose = FALSE
)

Arguments

target_genes

Character vector. GeneID(s) of the target genes.

gene_set_list

Named list of character vectors. Names should represent the gene sets, pathways, and the elements the genes within the respective gene set.

gene_universe

Optional character vector. If you would like to specify specifically the gene universe. If set to NULL, the function will default to all represented genes in the gene_set_list.

threshold

Float between 0 and 1 to filter on the fdr. Default: 0.05. If 1 everything is returned.

minimum_overlap

Number of minimum overlap between the target genes and the respective gene set.

.verbose

Boolean. Controls verbosity of the function.

Value

data.table with enrichment results.

Examples

# hypergeometric test of a target set against a small universe
gene_universe <- sprintf("gene_%03i", 1:200)
gene_sets <- list(
  set_a = gene_universe[1:20],
  set_b = gene_universe[15:40],
  set_c = gene_universe[100:130]
)
target <- gene_universe[c(1:12, 150:158)]
gse_hypergeometric(target, gene_sets, gene_universe, threshold = 1)
#>    gene_set_name odds_ratios       pvals          fdr  hits gene_set_lengths
#>           <char>       <num>       <num>        <num> <num>            <num>
#> 1:         set_a        28.5 4.19695e-09 1.259085e-08    12               20
#>    target_set_lengths
#>                 <int>
#> 1:                 21