Gene Ontology

phenol supports working with the GO in several following ways including some GO term enrichment analysis approaches.

Loading the data

To perform enrichment analysis, we require the GO ontology file, the annotation file, as well as a population set (e.g., all genes in a genome) and a study set (e.g., some set of genes determined to be differentially expressed).

Ontology gontology = OntologyLoader.loadOntology(new File(pathGoObo), "GO");
final GoGeneAnnotationParser annotparser = new GoGeneAnnotationParser(pathGoGaf);
List<TermAnnotation> goAnnots = annotparser.getTermAnnotations();
AssociationContainer associationContainer = new AssociationContainer(goAnnots);
Set<TermId> populationGenes = getPopulationSet(goAnnots);
StudySet populationSet = new StudySet(populationGenes,"population",associationContainer,gontology);
Set<TermId> studyGenes = ... // get list of genes from study set
StudySet studySet = new StudySet(studyGenes,"study",associationContainer,gontology);

Perform testing for overrepresentation

In this example, we show how to use the exact Fisher test to assess term overrepresentation.

Hypergeometric hgeo = new Hypergeometric();
MultipleTestingCorrection<Item2PValue> bonf = new Bonferroni<>();
TermForTermPValueCalculation tftpvalcal = new TermForTermPValueCalculation(gontology,
      associationContainer,
      populationSet,
      studySet,
      hgeo,
      bonf);

int popsize=populationGenes.size();
int studysize=studyGenes.size();
List<GoTerm2PValAndCounts> pvals = tftpvalcal.calculatePVals();
for (GoTerm2PValAndCounts item : pvals) {
  // output or do something else
}

See the implementation in GoEnrichmentDemo.java for more details.