GOEnrichment: GOEnrichmentHelpfile

Description

GOEnrichment is a function which, given as input an object of class DEGs, identifies overrepresented GO terms among differentially expressed genes. The analysis can be applied to all the GO ontologies or restricted to GO terms specifically belonging to one ontology: molecular function, cellular component or biological process. Moreover the function can identify enriched GO terms for separate classes of genes of interest: only up-regulated genes, only down-regulated genes or both of them together. The output of the function is an object of class GOsets, containing the results of the enrichment analysis.

Usage

GOEnrichment(object, ontology="all", classOfDEGs="both", test.method="classic", test.threshold = 0.05, mult.cor=TRUE)

Arguments

object

an object of class DEGs

ontology

a character string specifying the GO ontology of interest: CC for Cellular Component, BP for Biological Process, MF for Molecular Function or all for all the three ontologies. The default is set to all.

classOfDEGs

a character string specifying the class of genes for which we want to detect enriched GO terms: up for considering only up-regulated genes, down for considering only down-regulated genes, both for considering all DEGs, independently from the direction of their changes. The default is set to both.

test.method

a character string specifying the statistical method to calculate the enrichment. By default it is set to classic (enrichment is measured with the classic Fisher exact test), but it can also be set to elim, weight, weight01 or parentchild. All these methods are implemented in the topGO Bioconductor package

test.threshold

a numeric value specifying the significance threshold upon which the GO terms are considered significantly over-represented. By default it is se to 0.05.

mult.cor

a boolean variable specifying whether the significance threshold is applied to the multiple test corrected or to the original p-values obtained from the selected enrichment method. By default it is set to TRUE.

Value

An object of class GOsets

References

Ashburner M et al(2000). Gene ontology: tool for the unification of biology. Nat. Genet. May 2000;25(1):25-9.

Alexa A, Rahnenfuhrer J, Lengauer T. Improved scoring of functional groups from gene expression data by decorrelating go graph structure. Bioinformatics 2006, 22(13):1600-7

Examples

Run this code

data(tRanslatomeSampleData)
GOEnrichment(limma.DEGs,ontology="CC",classOfDEGs="up",
    test.method="classic", test.threshold = 0.05,mult.cor = TRUE)