enrichment: Perform Enrichment Analysis for a Single Gene Set

In pathfindR: Enrichment Analysis Utilizing Active Subnetworks

Perform Enrichment Analysis for a Single Gene Set

Description

Perform Enrichment Analysis for a Single Gene Set

Usage

enrichment(
  input_genes,
  genes_by_term = pathfindR.data::kegg_genes,
  term_descriptions = pathfindR.data::kegg_descriptions,
  adj_method = "bonferroni",
  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
genes_by_term	List that contains genes for each gene set. Names of this list are gene set IDs (default = kegg_genes)
term_descriptions	Vector that contains term descriptions for the gene sets. Names of this vector are gene set IDs (default = kegg_descriptions)
adj_method	correction method to be used for adjusting p-values. (default = 'bonferroni')
enrichment_threshold	adjusted-p value threshold used when filtering enrichment results (default = 0.05)
sig_genes_vec	vector of significant gene symbols. In the scope of this package, these are the input genes that were used for active subnetwork search
background_genes	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

See Also

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)
)

pathfindR documentation built on Oct. 9, 2023, 1:07 a.m.