Free Access Week - Data Engineering + BI
Data Engineering and BI courses are free this week!
Free Access Week - Jun 2-8

pathfindR (version 2.1.0)

enrichment: 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
)

Value

A data frame that contains enrichment results

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)

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

Run this code
enrichment(
  input_genes = c("PER1", "PER2", "CRY1", "CREB1"),
  sig_genes_vec = "PER1",
  background_genes = unlist(pathfindR.data::kegg_genes)
)

Run the code above in your browser using DataLab