Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology

Aaron J Masino, Elizabeth T Dechene, Matthew C Dulik, Alisha Wilkens, Nancy B Spinner, Ian D Krantz, Jeffrey W Pennington, Peter N Robinson, Peter S White

Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content.