getEnrichedGO {ChIPpeakAnno} | R Documentation

## Obtain enriched gene ontology (GO) terms that near the peaks

### Description

Obtain enriched gene ontology (GO) terms based on the features near the enriched peaks using GO.db package and GO gene mapping package such as org.Hs.db.eg to obtain the GO annotation and using hypergeometric test (phyper) and multtest package for adjusting p-values

### Usage

    getEnrichedGO(
      annotatedPeak,
      orgAnn,
      feature_id_type = "ensembl_gene_id",
      maxP = 0.01,
      minGOterm = 10,
      multiAdjMethod = NULL,
      condense = FALSE,
      removeAncestorByPval = NULL,
      keepByLevel = NULL
    )

### Arguments

`annotatedPeak` | A GRanges object or a vector of feature IDs
`orgAnn` | Organism annotation package such as org.Hs.eg.db for human and org.Mm.eg.db for mouse, org.Dm.eg.db for fly, org.Rn.eg.db for rat, org.Sc.eg.db for yeast and org.Dr.eg.db for zebrafish
`feature_id_type` | The feature type in annotatedPeak such as ensembl_gene_id, refseq_id, gene_symbol or entrez_id
`maxP` | The maximum p-value to be considered to be significant
`minGOterm` | The minimum count in a genome for a GO term to be included
`multiAdjMethod` | The multiple testing procedures, for details, see mt.rawp2adjp in multtest package
`condense` | Condense the results or not.
`removeAncestorByPval` | Remove ancestor by p-value. P-value is calculated by fisher exact test. If gene number in all of the children is significant greater than it in parent term, the parent term will be removed from the list.
`keepByLevel` | If the shortest path from the go term to 'all' is greater than the given level, the term will be removed.

### Value

A list with 3 elements

`list("bp")` | enriched biological process with the following 9 variables go.id:GO biological process id go.term:GO biological process term go.Definition:GO biological process description Ontology: Ontology branch, i.e. BP for biological process count.InDataset: count of this GO term in this dataset count.InGenome: count of this GO term in the genome pvalue: pvalue from the hypergeometric test totaltermInDataset: count of all GO terms in this dataset totaltermInGenome: count of all GO terms in the genome
`list("mf")` | enriched molecular function with the following 9 variables go.id:GO molecular function id go.term:GO molecular function term go.Definition:GO molecular function description Ontology: Ontology branch, i.e. MF for molecular function count.InDataset: count of this GO term in this dataset count.InGenome: count of this GO term in the genome pvalue: pvalue from the hypergeometric test totaltermInDataset: count of all GO terms in this dataset totaltermInGenome: count of all GO terms in the genome
`list("cc")` | enriched cellular component the following 9 variables go.id:GO cellular component id go.term:GO cellular component term go.Definition:GO cellular component description Ontology: Ontology type, i.e. CC for cellular component count.InDataset: count of this GO term in this dataset count.InGenome: count of this GO term in the genome pvalue: pvalue from the hypergeometric test totaltermInDataset: count of all GO terms in this dataset totaltermInGenome: count of all GO terms in the genome

### Author(s)

Lihua Julie Zhu

### References

Johnson, N. L., Kotz, S., and Kemp, A. W. (1992) Univariate Discrete Distributions, Second Edition. New York: Wiley

### See Also

phyper, hyperGtest

### Examples

      data(enrichedGO)
      enrichedGO$mf[1:10,]
      enrichedGO$bp[1:10,]
      enrichedGO$cc
      if (interactive()) {
         data(annotatedPeak)
         library(org.Hs.eg.db)
         library(GO.db)
         enriched.GO = getEnrichedGO(annotatedPeak[1:6,],
                                     orgAnn="org.Hs.eg.db",
                                     maxP=0.01,
                                     minGOterm=10,
                                     multiAdjMethod= NULL)
         dim(enriched.GO$mf)
         colnames(enriched.GO$mf)
         dim(enriched.GO$bp)
         enriched.GO$cc
    }

[Package ChIPpeakAnno version 3.24.2 Index]