genORA: Gene Over-Representation Enrichment Analysis

In GangLiLab/genekitr: Gene Analysis Toolkit

Gene Over-Representation Enrichment Analysis

Description

Gene Over-Representation Enrichment Analysis

Usage

genORA(
  id,
  geneset,
  group_list = NULL,
  padj_method = "BH",
  p_cutoff = 0.05,
  q_cutoff = 0.15,
  min_gset_size = 10,
  max_gset_size = 500,
  universe
)

Arguments

id	A vector of gene id which can be entrezid, ensembl, symbol or uniprot.
geneset	Gene set is a two-column data.frame with term id and gene id. Please use package 'geneset' to select available gene set or make new one.
group_list	A list of gene group information, default is NULL.
padj_method	One of "BH", "BY", "bonferroni","fdr","hochberg", "holm", "hommel", "none"
p_cutoff	Numeric of cutoff for both unadjusted and adjusted pvalue, default is 0.05.
q_cutoff	Numeric of cutoff for qvalue, default is 0.15.
min_gset_size	Numeric of minimal size of each geneset for analyzing, default is 10.
max_gset_size	Numeric of maximal size of each geneset for analyzing, default is 500.
universe	Character of background genes. If missing, all genes in geneset will be used as background.

Value

A 'data.frame'.

Examples

# only gene ids
data(geneList, package = "genekitr")
id <- names(geneList)[abs(geneList) > 1]
gs <- geneset::getGO(org = "human",ont = "mf",data_dir = tempdir())
ora <- genORA(id, geneset = gs)

# gene id with groups
id <- c(head(names(geneList), 50), tail(names(geneList), 50))
group <- list(
  group1 = c(rep("up", 50), rep("down", 50)),
  group2 = c(rep("A", 20), rep("B", 30))
)
gora <- genORA(id, geneset = gs, group_list = group)

GangLiLab/genekitr documentation built on Jan. 8, 2025, 6:40 a.m.