goEnrichment: Perform enrichment analysis of the given genes

In NoRCE: NoRCE: Noncoding RNA Sets Cis Annotation and Enrichment

Description

Perform enrichment analysis of the given genes

Usage

goEnrichment(
  genes,
  org_assembly = c("hg19", "hg38", "mm10", "dre10", "rn6", "dm6", "ce11", "sc3"),
  GOtype = c("BP", "CC", "MF"),
  pCut = 0.05,
  pAdjCut = 0.05,
  pAdjust = c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none"),
  min = 5,
  backG = "",
  backGType = "pc_gene",
  enrichTest = c("hyper", "binom", "fisher", "chi")
)

Arguments

genes	Set of input genes. Supported format HUGO.
org_assembly	Genome assembly of interest for the analysis. Possible assemblies are "mm10" for mouse, "dre10" for zebrafish, "rn6" for rat, "dm6" for fruit fly, "ce11" for worm, "sc3" for yeast, "hg19" and "hg38" for human
GOtype	Hierarchical category of the GO ontology. Possible values are "BP"(default), "CC", "MF".
pCut	Threshold value for the pvalue. Default value is 0.05
pAdjCut	Cutoff value for the adjusted p-values using one of given method. Default value is 0.05.
pAdjust	Methods of the adjusted p-values. Possible methods are "bonferroni", "holm", "BH"(default)
min	Minimum number of gene that are required for enrichment. By default, it is set to 5
backG	The set of genes that tested against to the input (background gene)
backGType	Type of the background gene. If miRNA gene set is used for background gene, backGType should be set to the 'mirna'
enrichTest	Types of enrichment methods to perform enrichment analysis. Possible values are "hyper"(default), "binom", "fisher", "chi".

Value

GO enrichment results

Examples

subsetGene <- breastmRNA[1:30,]
breastEnr <- goEnrichment(genes = subsetGene,
                          org_assembly = 'hg19',
                          GOtype = 'MF',
                          min = 2)

NoRCE documentation built on Nov. 8, 2020, 7:17 p.m.