title: Impact of ontology evolution on functional analyses.
abstract: BACKGROUND
  Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes.
  
  
  RESULTS
  Our results show that past changes in the GO are non-uniformly distributed over different branches of the ontology. Considering the semantic relatedness of significant categories in analysis results allows a more realistic stability assessment for functional enrichment studies. We observe that the results of term-enrichment analyses tend to be surprisingly stable despite changes in ontology and annotation.
authors.affiliation: Department of Computer Science, University of Leipzig, Leipzig, Germany. gross@informatik.uni-leipzig.de
authors.forename: Anika
authors.initials: A
authors.lastname: Groß
authors.forename: Michael
authors.initials: M
authors.lastname: Hartung
authors.forename: Kay
authors.initials: K
authors.lastname: Prüfer
authors.forename: Janet
authors.initials: J
authors.lastname: Kelso
authors.forename: Erhard
authors.initials: E
authors.lastname: Rahm
mesh_terms: D000818:Animals; D005796:Genes; D058977:Molecular Sequence Annotation; D011323:Primates; D012377:Rodentia / Q000235:genetics; D018875:Vocabulary, Controlled