Mapping Phenotype Ontologies for Obesity and Diabetes
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Mapping Phenotype Ontologies for Obesity and Diabetes
- 1. Mapping Phenotype Ontologies Chris Mungall Monarch Initiative http://monarchinitiative.org Lawrence Berkeley National Laboratory PhenoBridges Workshop 2013
- 2. Outline • Problem: multiple ontologies of relevance to the obesity/diabetes domain – By species – By category – How can we bring these together? • Bridging ontologies using OWL axioms – Enables cross-domain semantic queries • Integrated ontology-data views in Monarch • Challenges – Modeling strategies – Tools
- 3. Ontologies for phenotype and disease gene 1 gene 2 disease A disease B Tools: • OWLSim • BOQA • PhenoDigm / MouseFinder • Phenomizer • Phenomenet
- 4. We want to bridge species Washington, N. L., Haendel, M. A., Mungall, C. J., Ashburner, M., Westerfield, M., & Lewis, S. E. (2009). Linking Human Diseases to Animal Models Using Ontology- Based Phenotype Annotation. PLoS Biol, 7(11). doi:10.1371/journal.pbio.1000247
- 5. Bridging across species requires bridging across ontologies gene 1 gene 2 disease A disease B HP:0012093 Abnormality of endocrine pancreas physiology MP:0009165 abnormal endocrine pancreas morphology ? ?
- 6. Mammalian Phenotype Ontology Smith, C. L., Goldsmith, Carroll-A. W., & Eppig, J. T. (2005). The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information. Genome Biol, 6(1). doi:10.1186/gb-2004-6-1-r7 Used to annotate and query: • Genotypes • Alleles • Genes In mice abnormal pancreatic beta cell mass abnormal pancreatic beta cell morphology abnormal pancreatic islet morphology abnormal endocrine pancreas morphology abnormal pancreatic beta cell differentiation abnormal pancreatic alpha cell morphology abnormal pancreatic alpha cell differentiation abnormal pancreatic alpha cell number
- 7. Human Phenotype Ontology Robinson, P. N. P. N., Koehler, S., Bauer, S., Seelow, D., Horn, D., Mundlos, S., K{"o}hler, S., et al. (2008). The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. American Journal of Human Genetics, 83(5), 610-615. Elsevier. doi:10.1016/j.ajhg.2008.09.017 Used to annotate: • Patients • Disorders • Genotypes • Genes • Sequence variants In human Reduced pancreatic beta cells Abnormality of pancreatic islet cells Abnormality of endocrine pancreas physiology Pancreatic islet cell adenoma Pancreatic islet cell adenoma Insulinoma Multiple pancreatic beta-cell adenomas Abnormality of exocrine pancreas physiology
- 8. Issue: bridging across categories/perspectives MP:0005217 abnormal pancreatic beta- cell morphology GO:0003309 pancreatic B cell differentiation ?
- 9. Phenotypes require more than “phenotype ontologies” glucose metabolism (GO:0006006 ) Gene/protein function data glucose (CHEBI:172 34) Metabolomics, t oxicogenomics Data Disease & phenotype data type II diabetes mellitus (DOID:9352) pyruvate (CHEBI:153 61) DISEASE GO CHEBI pancreatic beta cell (CL:0000169) transcriptomic data CL
- 10. Bridging via lexical methods • Approach – Create pairwise mappings between ontologies – Use lexical methods and/or curation • Advantages: – Large body of tools and willing text miners • Disadvantages: – Semantics-free – Machine doesn‟t understand text – Inexact matches
- 11. Reduced pancreatic beta cells Abnormality of pancreatic islet cells Abnormality of endocrine pancreas physiology Pancreatic islet cell adenoma Pancreatic islet cell adenoma Insulinoma Multiple pancreatic beta-cell adenomas Abnormality of exocrine pancreas physiology abnormal pancreatic beta cell mass abnormal pancreatic beta cell morphology abnormal pancreatic islet morphology abnormal endocrine pancreas morphology abnormal pancreatic beta cell number abnormal pancreatic alpha cell morphology abnormal pancreatic alpha cell differentiation abnormal pancreatic alpha cell number
- 12. Enhance lexical approach with OWL bridging axioms • Key idea: – Describe the phenotype in a machine- interpretable way • Break it down into digestible chunks! • Logical definition – The machine will then be able to help you • Match phenotypes • Automate ontology checking and addition of new terms • Approach: – Use Web Ontology Language (OWL), a description logic to describe phenotypes – Use OWL reasoning to find connections Mungall, C. J., Gkoutos, G., Washington, N., & Lewis, S. (2007). Representing Phenotypes in OWL. In C. Golbreich, A. Kalyanpur, & B. Parsia (Eds.), Proceedings of the OWLED 2007 Workshop on OWL: Experience and Directions. Innsbruck, Austria. http://www.webont.org/owled/2007/PapersPDF/paper_40.pdf
- 13. abnormal pancreatic beta cell mass abnormal pancreatic beta cell morphology abnormal pancreatic islet morphology type B pancreatic cell islet of Langerhans endocrine pancreas part of part of abnormal endocrine pancreas morphology part of
- 14. abnormal pancreatic beta cell mass abnormal pancreatic beta cell morphology abnormal pancreatic islet morphology type B pancreatic cell islet of Langerhans endocrine pancreas part of part of abnormal endocrine pancreas morphology part of mass morphology quality
- 15. abnormal pancreatic beta cell mass abnormal pancreatic beta cell morphology abnormal pancreatic islet morphology type B pancreatic cell islet of Langerhans endocrine pancreas part of part of abnormal endocrine pancreas morphology part of mass morphology quality Class: „abnormal pancreatic beta cell mass‟ EquivalentTo: „abnormal phenotype‟ and has_entity some „type B pancreatic cell‟ and has_quality some mass
- 16. Reduced pancreatic beta cells Abnormality of pancreatic islet cells Abnormality of endocrine pancreas physiology Pancreatic islet cell adenoma Pancreatic islet cell adenoma Insulinoma Multiple pancreatic beta-cell adenomas Abnormality of exocrine pancreas physiology abnormal pancreatic beta cell mass abnormal pancreatic beta cell morphology abnormal pancreatic islet morphology abnormal endocrine pancreas morphology abnormal pancreatic beta cell number abnormal pancreatic alpha cell morphology abnormal pancreatic alpha cell differentiation abnormal pancreatic alpha cell number inferred from CL inferred from PATO „abnormal phenotype‟ and has_entity some „type B pancreatic cell‟ and has_quality some amount „abnormal phenotype‟ and has_entity some „type B pancreatic cell‟ and has_quality some „reduced amount‟
- 17. Mungall, C. J., Gkoutos, G., Smith, C., Haendel, M., Lewis, S., & Ashburner, M. (2010). Integrating phenotype ontologies across multiple species. Genome Biology, 11(1), R2. doi:10.1186/gb-2010-11-1-r2 Köhler, S., Doelken, S. C., Ruef, B. J., Bauer, S., Washington, N., Westerfield, M., Gkoutos, G., et al. (2013). Construction and accessibility of a cross- species phenotype ontology along with gene annotations for biomedical research. F1000Research, 1–12. doi:10.3410/f1000research.2-30.v1 7181 / 9022 MP Terms are described
- 18. Phenotypes to metabolites glucose homeostasis (GO:0042593) ≡ homeostasis (GO:0042592) glucose (CHEBI:17234) ⊓ ∃.has_participant http://wiki.geneontology.org/index.php/Ontology_extensions abnormal glucose homeostasis (MP:0002078)
- 19. Linking cell types to proteins via GO ≡ secretion (GO:0046903) insulin (PR:000009054) ⊓ ∃.has_output ⊑pancreatic beta cell (CL:0000169) Insulin secretion (GO:0046903) ∃.capable_of INS_HUMAN - P01308 Meehan, T., Masci, A. M., Abdulla, A., Cowell, L., Blake, J., Mungall, C. J., & Diehl, A. (2011). Logical Development of the Cell Ontology. BMC Bioinformatics, 12(1), 6. doi:10.1186/1471-2105-12-6
- 20. Uberon bridges single species anatomy ontologies Mungall, C. J., Torniai, C., Gkoutos, G. V., Lewis, S. E., & Haendel, M. A. (2012). Uberon, an integrative multi-species anatomy ontology. Genome Biology, 13(1), R5. doi:10.1186/gb-2012-13-1-r5
- 21. Lexical methods • Obol : grammar approach • Entity matching Curation • Edit bridge files • Edit source ontologies OWL Reasoning • Elk • GULO • Jenkins Iterative development and deployment Kohler, S., Bauer, S., Mungall, C. J., Carletti, G., Smith, C. L., Schofield, P., Gkoutos, G. V, et al. (2011). Improving ontologies by automatic reasoning and evaluation of logical definitions. BMC Bioinformatics, 12(1), 418. doi:10.1186/1471-2105-12-418 Mungall, C. J., Dietze, H., Carbon, S. J., Ireland, A., Bauer, S., & Lewis, S. (2012). Continuous Integration of Open Biological Ontology Libraries. Bio-Ontologies 2012 http://bio-ontologies.knowledgeblog.org/405
- 22. Integrated views in Monarch http://monarchinitiative.org Linking model systems to human diseases
- 23. Integrated views in Monarch http://monarchinitiative.org glucose metabolism (GO:0006006 ) Gene/protein function data glucose (CHEBI:172 34) Metabolomics, toxicogenomics Data Disease & phenotype data type II diabetes mellitus (DOID:9352) pyruvate (CHEBI:153 61) DISEASE/ PHENOTYPE GO CHEBI pancreatic beta cell (CL:0000169) transcriptomic data CL
- 24. Roadblocks and pitfalls • Lack of tool support for ontology development • Many tools for „mapping after the fact‟ – Mapping should not be retrospective – Must be integrated into ontology development lifecycle • OWL Modeling pitfalls – Over-modeling – Under-modeling
- 25. Overcoming ontology development bottlenecks with TermGenie • Developed for GO – Instant compositional terms for curators – OWL axioms are added at time of term creation • We are rolling out pheno-ontology instances – Trial run on FYPO and plant traits http://termgenie.org
- 26. Modeling confusion and analysis paralysis • absent pancreatic beta cells (MP:0009174) – Tempting to use OWL cardinality • Does this represent the biology? • decreased pancreatic beta cell number (MP:0003339) – Can‟t do this with OWL cardinality! • Lesson: don‟t over-model in OWL
- 27. Modeling temporal progression • How did there come to be absence of beta cells in the pancreas? • What are the downstream effects? • Changes with ages – Hyperglycemic hypoglycemic • Existing phenotype ontologies steer clear of causality – Next frontier
- 28. What I haven‟t talked about • Quantitative phenotypes • Assay vs phenotype • Behavioral phenotypes • Environments • Mining disease phenotypes from the literature • Clinical vocabularies (see Nathalie‟s talk) • Modeling other model systems • The data! • Making use of the data and OWL axioms for analysis (see Damian‟s talk) • …a lot more
- 29. Questions/Summary • Approaches to mapping – OWL bridging axioms • Roadblocks and pitfalls – OWL modeling analysis paralysis – Lack of tool support – Need to push upstream in ontology engineering lifecycle – Modeling complex phenomena • From observation to temporal progression and models of causality • Tools – CrossSpeciesPheno – Available: • GULO, TermGenie, OBO-Edit, Protégé 4, OWL Reasoners, Onto- Jenkins – Required: integration upstream
- 30. • Charite – Sebastian Kohler – Sandra Doelken – Sebatian Bauer – Peter Robinson • U of Oregon – Barbara Ruef – Monte Westerfield • OHSU – Carlo Torniai – Nicole Vasilesky – Shahim Essaid – Matt Brush – Melissa Haendel • Sanger – Anika Oehlrich – Damian Smedley • University of Cambridge – George Gkoutos – Rob Hoehndorf – Paul Schofield • Lawrence Berkeley – Nicole Washington – Suzanna Lewis • UCSD – Amarnath Gupta – Jeff Grethe – Anita Bandrowski – Maryann Martone • U of Pitt – Chuck Borneo – Harry Hochheiser • JAX – Terry Meehan – Cynthia Smith Acknowledgments
Hinweis der Redaktion
- Without additional knowledge, computers can’t make the connections.Show this crumbling.Show uberon.
- Equivalence axioms