Measuring phenotype semantic similarity using Human Phenotype Ontology

Abstract

It is critical yet remains to be challenging to make right disease diagnosis based on complex clinical characteristic and heterogeneous genetic background. Recently, Human Phenotype Ontology (HPO)-based phenotype similarity has been widely used to aid disease diagnosis. However, the existing measurements are revised based on the Gene Ontology-based term similarity models, which are not optimized for human phenotype ontologies. We propose a new similarity measure called PhenoSim. Our model includes a noise reduction component to model the noisy patient phenotype data, and a path-constrained Information Content-based method for measuring phenotype semantics similarity. Evaluation tests showed that PhenoSim could improve the performance of HPO-based phenotype similarity measurement.