Perform Enrichment Analysis for a Single Gene Set

enrichment(
input_genes,
genes_by_term = pathfindR.data::kegg_genes,
term_descriptions = pathfindR.data::kegg_descriptions,
enrichment_threshold = 0.05,
sig_genes_vec,
background_genes
)

Arguments

input_genes The set of gene symbols to be used for enrichment analysis. In the scope of this package, these are genes that were identified for an active subnetwork List that contains genes for each gene set. Names of this list are gene set IDs (default = kegg_genes) Vector that contains term descriptions for the gene sets. Names of this vector are gene set IDs (default = kegg_descriptions) correction method to be used for adjusting p-values. (default = "bonferroni") adjusted-p value threshold used when filtering enrichment results (default = 0.05) vector of significant gene symbols. In the scope of this package, these are the input genes that were used for active subnetwork search vector of background genes. In the scope of this package, the background genes are taken as all genes in the PIN (see enrichment_analyses)

Value

A data frame that contains enrichment results

p.adjust for adjustment of p values. See run_pathfindR for the wrapper function of the pathfindR workflow. hyperg_test for the details on hypergeometric distribution-based hypothesis testing.

Examples

enrichment(input_genes = c("PER1", "PER2", "CRY1", "CREB1"),
sig_genes_vec = "PER1",
background_genes = unlist(pathfindR.data::kegg_genes))
#>                ID      Term_Description Fold_Enrichment      p_value
#> hsa04710 hsa04710      Circadian rhythm       1062.1290 6.426318e-13
#> hsa04713 hsa04713 Circadian entrainment        339.4433 9.892777e-08