Logo image
The human phenotype ontology: Semantic unification of common and rare disease
Journal article   Open access   Peer reviewed

The human phenotype ontology: Semantic unification of common and rare disease

T. Groza, S. Kohler, D. Moldenhauer, N. Vasilevsky, G. Baynam, T. Zemojtel, L.M. Schriml, W.A. Kibbe, P.N. Schofield, T. Beck, …
The American Journal of Human Genetics, Vol.97(1), pp.111-124
2015
pdf
phenotype_ontology.pdfDownloadView
Published (Version of Record) Open Access
url
Free to Read *No subscription requiredView

Abstract

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available.

Details

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

Source: InCites

Metrics

217 File views/ downloads
99 Record Views

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types
Domestic collaboration
International collaboration
Citation topics
1 Clinical & Life Sciences
1.54 Molecular & Cell Biology - Genetics
1.54.79 Genomic Bioinformatics
Web Of Science research areas
Genetics & Heredity
ESI research areas
Molecular Biology & Genetics
Logo image