The human phenotype ontology in 2017

Sebastian Köhler, Nicole A. Vasilevsky, Mark Engelstad, Erin Foster, Julie McMurry, Ségolène Aymé, Gareth Baynam, Susan M. Bello, Cornelius F. Boerkoel, Kym M. Boycott, Michael Brudno, Orion J. Buske, Patrick F. Chinnery, Valentina Cipriani, Laureen E. Connell, Hugh J.S. Dawkins, Laura E. DeMare, Andrew D. Devereau, Bert B.A. De Vries, Helen V. FirthKathleen Freson, Daniel Greene, Ada Hamosh, Ingo Helbig, Courtney Hum, Johanna A. Jähn, Roger James, Roland Krause, Stanley J.F. Laulederkind, Hanns Lochmüller, Gholson J. Lyon, Soichi Ogishima, Annie Olry, Willem H. Ouwehand, Nikolas Pontikos, Ana Rath, Franz Schaefer, Richard H. Scott, Michael Segal, Panagiotis I. Sergouniotis, Richard Sever, Cynthia L. Smith, Volker Straub, Rachel Thompson, Catherine Turner, Ernest Turro, Marijcke W.M. Veltman, Tom Vulliamy, Jing Yu, Julie Von Ziegenweidt, Andreas Zankl, Stephan Züchner, Tomasz Zemojtel, Julius O.B. Jacobsen, Tudor Groza, Damian Smedley, Christopher J. Mungall, Melissa Haendel, Peter N. Robinson

Research output: Contribution to journalArticlepeer-review

408 Scopus citations


Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human PhenotypeOntology (HPO; project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.

Original languageEnglish (US)
Pages (from-to)D865-D876
JournalNucleic acids research
Issue numberD1
StatePublished - Jan 1 2017

ASJC Scopus subject areas

  • Genetics


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