title: INVESTIGATING THE IMPORTANCE OF ANATOMICAL HOMOLOGY FOR CROSS-SPECIES PHENOTYPE COMPARISONS USING SEMANTIC SIMILARITY. Accepted at Pacific Symposium on Biocomputing, 2016.
abstract: There is growing use of ontologies for the measurement of cross-species phenotype similarity. Such similarity measurements contribute to diverse applications, such as identifying genetic models for human diseases, transferring knowledge among model organisms, and studying the genetic basis of evolutionary innovations. Two organismal features, whether genes, anatomical parts, or any other inherited feature, are considered to be homologous when they are evolutionarily derived from a single feature in a common ancestor. A classic example is the homology between the paired fins of fishes and vertebrate limbs. Anatomical ontologies that model the structural relations among parts may fail to include some known anatomical homologies unless they are deliberately added as separate axioms. The consequences of neglecting known homologies for applications that rely on such ontologies has not been well studied. Here, we examine how semantic similarity is affected when external homology knowledge is included. We measure phenotypic similarity between orthologous and non-orthologous gene pairs between humans and either mouse or zebrafish, and compare the inclusion of real with faux homology axioms. Semantic similarity was preferentially increased for orthologs when using real homology axioms, but only in the more divergent of the two species comparisons (human to zebrafish, not human to mouse), and the relative increase was less than 1% to non-orthologs. By contrast, inclusion of both real and faux random homology axioms preferentially increased similarities between genes that were initially more dissimilar in the other comparisons. Biologically meaningful increases in semantic similarity were seen for a select subset of gene pairs. Overall, the effect of including homology axioms on cross-species semantic similarity was modest at the levels of divergence examined here, but our results hint that it may be greater for more distant species comparisons.
authors.affiliation: Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA, manda.prashanti@gmail.com.
authors.forename: Prashanti
authors.initials: P
authors.lastname: Manda
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Mungall
authors.forename: James P
authors.initials: JP
authors.lastname: Balhoff
authors.forename: Hilmar
authors.initials: H
authors.lastname: Lapp
authors.forename: Todd J
authors.initials: TJ
authors.lastname: Vision
mesh_terms: D000717:Anatomy, Comparative / Q000379:methods* / Q000706:statistics & numerical data; D000818:Animals; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D019143:Evolution, Molecular; D006801:Humans; D051379:Mice; D010641:Phenotype; D012660:Semantics; D012689:Sequence Homology, Nucleic Acid; D013045:Species Specificity; D018511:Systems Integration; D015027:Zebrafish / Q000033:anatomy & histology / Q000235:genetics