Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics

Sebastian Köhler, N. Christine Øien, Orion J. Buske, Tudor Groza, Julius O.B. Jacobsen, Craig McNamara, Nicole Vasilevsky, Leigh C. Carmody, J. P. Gourdine, Michael Gargano, Julie A. McMurry, Daniel Danis, Christopher J. Mungall, Damian Smedley, Melissa Haendel, Peter N. Robinson

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


The Human Phenotype Ontology (HPO) is a standardized set of phenotypic terms that are organized in a hierarchical fashion. It is a widely used resource for capturing human disease phenotypes for computational analysis to support differential diagnostics. The HPO is frequently used to create a set of terms that accurately describe the observed clinical abnormalities of an individual being evaluated for suspected rare genetic disease. This profile is compared with computational disease profiles in the HPO database with the aim of identifying genetic diseases with comparable phenotypic profiles. The computational analysis can be coupled with the analysis of whole-exome or whole-genome sequencing data through applications such as Exomiser. This article explains how to choose an optimal set of HPO terms for these cases and enter them with software, such as PhenoTips and PatientArchive, and demonstrates how to use Phenomizer and Exomiser to generate a computational differential diagnosis.

Original languageEnglish (US)
Article numbere92
JournalCurrent protocols in human genetics
Issue number1
StatePublished - Sep 2019


  • HPO
  • Human Phenotype Ontology
  • differential diagnosis
  • exome
  • phenotype

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)


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