module_enrichment {BioNERO}R Documentation

Perform enrichment analysis for coexpression network modules

Description

Perform enrichment analysis for coexpression network modules

Usage

module_enrichment(
  net = NULL,
  background_genes,
  annotation,
  column = NULL,
  correction = "BH",
  p = 0.05,
  bp_param = BiocParallel::SerialParam()
)

Arguments

net

List object returned by exp2gcn.

background_genes

Character vector of genes to be used as background for the Fisher's Exact Test.

annotation

Annotation data frame with genes in the first column and functional annotation in the other columns. This data frame can be exported from Biomart or similar databases.

column

Column or columns of annotation to be used for enrichment. Both character or numeric values with column indices can be used. If users want to supply more than one column, input a character or numeric vector. Default: all columns from annotation.

correction

Multiple testing correction method. One of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr" or "none". Default is "BH".

p

P-value threshold. P-values below this threshold will be considered significant. Default is 0.05.

bp_param

BiocParallel back-end to be used. Default: BiocParallel::SerialParam()

Value

A data frame containing enriched terms, p-values, gene IDs and module names.

Author(s)

Fabricio Almeida-Silva

Examples


data(filt.se)
data(zma.interpro)
background <- rownames(filt.se)
gcn <- exp2gcn(filt.se, SFTpower = 18, cor_method = "pearson")
mod_enrich <- module_enrichment(gcn, background, zma.interpro, p=1)


[Package BioNERO version 1.0.4 Index]