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The Unified Phenotype Ontology : a framework for cross-species integrative phenomics

Journal Article · · Genetics (Online)
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  1. Semanticly (Greece)
  2. Jackson Laboratory, Bar Harbor, ME (United States)
  3. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI) (United Kingdom)
  4. King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)
  5. University of North Carolina, Chapel Hill, NC (United States)
  6. Univ. of Oslo (Norway)
  7. Univ. of Oregon, Eugene, OR (United States)
  8. Queen Mary Univ. of London (United Kingdom)
  9. Columbia Univ., New York, NY (United States). Irving Medical Center
  10. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
  11. Rothamsted Research (United Kingdom)
  12. Stanford Univ., CA (United States)
  13. Northwestern Univ., Evanston, IL (United States)
  14. Cincinnati Children's Hospital Medical Center, OH (United States)
  15. California Institute of Technology (CalTech), Pasadena, CA (United States)
  16. Berlin Institute of Health at Charité (Germany)
  17. Univ. of Cambridge (United Kingdom)
  18. Ada Health, Berlin (Germany)
  19. World Conservation Monitoring Centre (United Kingdom)
  20. Univ. of Colorado, Aurora, CO (United States)
  21. Stowers Institute for Medical Research, Kansas City, MO (United States)
  22. Berlin Institute of Health at Charité, Berlin (Germany)
  23. Critical Path Institute, Tucson, AZ (United States)
  24. Wellcome Sanger Institute (United Kingdom)
+ Show Author Affiliations
Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
2531008
Alternate ID(s):
OSTI ID: 2553903
Journal Information:
Genetics (Online), Journal Name: Genetics (Online) Journal Issue: 3 Vol. 229; ISSN 1943-2631
Publisher:
Oxford University Press; Genetics Society of AmericaCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

59 BASIC BIOLOGICAL SCIENCES
96 KNOWLEDGE MANAGEMENT AND PRESERVATION
integration
ontology
phenotype
semantics