The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

Sebastian Köhler, Sandra C Doelken, Christopher J Mungall, Sebastian Bauer, Helen V Firth, Isabelle Bailleul-Forestier, Graeme C M Black, Danielle L Brown, Michael Brudno, Jennifer Campbell, David R FitzPatrick, Janan T Eppig, Andrew P Jackson, Kathleen Freson, Marta Girdea, Ingo Helbig, Jane A Hurst, Johanna Jähn, Laird G Jackson, Anne M Kelly, David H Ledbetter, Sahar Mansour, Christa L Martin, Celia Moss, Andrew Mumford, Willem H Ouwehand, Soo-Mi Park, Erin Rooney Riggs, Richard H Scott, Sanjay Sisodiya, Steven Van Vooren, Ronald J Wapner, Andrew O M Wilkie, Caroline F Wright, Anneke T Vulto-van Silfhout, Nicole de Leeuw, Bert B A de Vries, Nicole L Washingthon, Cynthia L Smith, Monte Westerfield, Paul Schofield, Barbara J Ruef, Georgios V Gkoutos, Melissa Haendel, Damian Smedley, Suzanna E Lewis, Peter N Robinson

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.