Mapping Phenotype Ontologies for Obesity and Diabetes
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Mapping Phenotype Ontologies for Obesity and Diabetes

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  • Without additional knowledge, computers can’t make the connections.Show this crumbling.Show uberon.
  • Equivalence axioms

Mapping Phenotype Ontologies for Obesity and Diabetes Mapping Phenotype Ontologies for Obesity and Diabetes Presentation Transcript

  • Mapping PhenotypeOntologiesChris MungallMonarch Initiativehttp://monarchinitiative.orgLawrence Berkeley National LaboratoryPhenoBridges Workshop 2013
  • Outline• Problem: multiple ontologies of relevance tothe 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
  • Ontologies for phenotype anddiseasegene 1gene 2diseaseAdiseaseBTools:• OWLSim• BOQA• PhenoDigm / MouseFinder• Phenomizer• Phenomenet
  • We want to bridge speciesWashington, 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
  • Bridging across speciesrequires bridging acrossontologiesgene 1gene 2diseaseAdiseaseBHP:0012093Abnormality of endocrine pancreas physiologyMP:0009165abnormal endocrine pancreas morphology??
  • Mammalian Phenotype OntologySmith, C. L., Goldsmith, Carroll-A. W., &Eppig, J. T. (2005). The MammalianPhenotype Ontology as a tool forannotating, analyzing and comparingphenotypic information. GenomeBiol, 6(1). doi:10.1186/gb-2004-6-1-r7Used to annotate and query:• Genotypes• Alleles• GenesIn miceabnormalpancreaticbeta cellmassabnormalpancreaticbeta cellmorphologyabnormalpancreatic isletmorphologyabnormalendocrinepancreasmorphologyabnormalpancreaticbeta celldifferentiationabnormalpancreaticalpha cellmorphologyabnormalpancreaticalpha celldifferentiationabnormalpancreaticalpha cellnumber
  • Human Phenotype OntologyRobinson, P. N. P.N., Koehler, S., Bauer, S., Seelow, D., Horn, D., Mundlos, S., K{"o}hler, S., et al. (2008). TheHuman Phenotype Ontology: a tool for annotating and analyzing human hereditarydisease. American Journal of Human Genetics, 83(5), 610-615. Elsevier.doi:10.1016/j.ajhg.2008.09.017Used to annotate:• Patients• Disorders• Genotypes• Genes• Sequence variantsIn humanReduced pancreaticbeta cellsAbnormality ofpancreatic isletcellsAbnormality of endocrinepancreas physiologyPancreatic isletcell adenomaPancreatic islet celladenomaInsulinomaMultiple pancreaticbeta-cell adenomasAbnormality of exocrinepancreas physiology
  • Issue: bridging acrosscategories/perspectivesMP:0005217abnormal pancreatic beta-cell morphologyGO:0003309pancreatic B cell differentiation?
  • Phenotypes require more than“phenotype ontologies”glucosemetabolism(GO:0006006)Gene/proteinfunction dataglucose(CHEBI:17234)Metabolomics, toxicogenomicsDataDisease &phenotypedatatype IIdiabetesmellitus(DOID:9352)pyruvate(CHEBI:15361)DISEASE GO CHEBIpancreaticbeta cell(CL:0000169)transcriptomicdataCL
  • Bridging via lexical methods• Approach– Create pairwise mappings betweenontologies– 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
  • Reduced pancreaticbeta cellsAbnormality ofpancreatic isletcellsAbnormality of endocrinepancreas physiologyPancreatic isletcell adenomaPancreatic islet celladenomaInsulinomaMultiple pancreaticbeta-cell adenomasAbnormality of exocrinepancreas physiologyabnormalpancreaticbeta cellmassabnormalpancreaticbeta cellmorphologyabnormalpancreatic isletmorphologyabnormalendocrinepancreasmorphologyabnormalpancreaticbeta cellnumberabnormalpancreaticalpha cellmorphologyabnormalpancreaticalpha celldifferentiationabnormalpancreaticalpha cellnumber
  • Enhance lexical approach withOWL 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), adescription logic to describe phenotypes– Use OWL reasoning to find connectionsMungall, 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
  • abnormalpancreaticbeta cellmassabnormalpancreaticbeta cellmorphologyabnormalpancreatic isletmorphologytype BpancreaticcellisletofLangerhansendocrinepancreaspartofpartofabnormalendocrinepancreasmorphologypartof
  • abnormalpancreaticbeta cellmassabnormalpancreaticbeta cellmorphologyabnormalpancreatic isletmorphologytype BpancreaticcellisletofLangerhansendocrinepancreaspartofpartofabnormalendocrinepancreasmorphologypartofmassmorphologyquality
  • abnormalpancreaticbeta cellmassabnormalpancreaticbeta cellmorphologyabnormalpancreatic isletmorphologytype BpancreaticcellisletofLangerhansendocrinepancreaspartofpartofabnormalendocrinepancreasmorphologypartofmassmorphologyqualityClass: „abnormal pancreatic beta cell mass‟EquivalentTo: „abnormal phenotype‟ andhas_entity some „type B pancreatic cell‟ andhas_quality some mass
  • Reduced pancreaticbeta cellsAbnormality ofpancreatic isletcellsAbnormality of endocrinepancreas physiologyPancreatic isletcell adenomaPancreatic islet celladenomaInsulinomaMultiple pancreaticbeta-cell adenomasAbnormality of exocrinepancreas physiologyabnormalpancreaticbeta cellmassabnormalpancreaticbeta cellmorphologyabnormalpancreatic isletmorphologyabnormalendocrinepancreasmorphologyabnormalpancreaticbeta cellnumberabnormalpancreaticalpha cellmorphologyabnormalpancreaticalpha celldifferentiationabnormalpancreaticalpha cellnumberinferredfrom CLinferredfrom PATO„abnormal phenotype‟ andhas_entity some „type B pancreatic cell‟ andhas_quality some amount„abnormal phenotype‟ andhas_entity some „type B pancreatic cell‟ andhas_quality some „reduced amount‟
  • Mungall, C.J., Gkoutos, G., Smith, C., Haendel, M., Lewis, S., &Ashburner, M. (2010). Integrating phenotype ontologiesacross multiple species. Genome Biology, 11(1), R2.doi:10.1186/gb-2010-11-1-r2Köhler, 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 annotationsfor biomedical research. F1000Research, 1–12.doi:10.3410/f1000research.2-30.v17181 / 9022 MPTerms are described
  • Phenotypes to metabolitesglucose homeostasis(GO:0042593) ≡homeostasis(GO:0042592)glucose(CHEBI:17234)⊓∃.has_participanthttp://wiki.geneontology.org/index.php/Ontology_extensionsabnormal glucosehomeostasis(MP:0002078)
  • Linking cell types to proteins viaGO≡secretion(GO:0046903)insulin(PR:000009054)⊓∃.has_output⊑pancreatic beta cell(CL:0000169)Insulin secretion(GO:0046903)∃.capable_ofINS_HUMAN - P01308Meehan, T., Masci, A.M., Abdulla, A., Cowell, L., Blake, J., Mungall, C. J., & Diehl, A.(2011). Logical Development of the Cell Ontology. BMCBioinformatics, 12(1), 6. doi:10.1186/1471-2105-12-6
  • Uberon bridges single speciesanatomy ontologiesMungall, C. J., Torniai, C., Gkoutos, G. V., Lewis, S. E., & Haendel, M. A. (2012). Uberon, an integrativemulti-species anatomy ontology. Genome Biology, 13(1), R5. doi:10.1186/gb-2012-13-1-r5
  • Lexicalmethods• Obol :grammarapproach• EntitymatchingCuration• Edit bridge files• Edit source ontologiesOWLReasoning• Elk• GULO• JenkinsIterative development and deploymentKohler, S., Bauer, S., Mungall, C. J., Carletti, G., Smith, C. L., Schofield, P., Gkoutos, G. V, et al. (2011). Improving ontologies by automaticreasoning and evaluation of logical definitions. BMC Bioinformatics, 12(1), 418. doi:10.1186/1471-2105-12-418Mungall, 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
  • Integrated views in Monarchhttp://monarchinitiative.orgLinking model systems tohuman diseases
  • Integrated views in Monarchhttp://monarchinitiative.orgglucosemetabolism(GO:0006006)Gene/proteinfunction dataglucose(CHEBI:17234)Metabolomics,toxicogenomicsDataDisease &phenotypedatatype IIdiabetesmellitus(DOID:9352)pyruvate(CHEBI:15361)DISEASE/PHENOTYPEGO CHEBIpancreaticbeta cell(CL:0000169)transcriptomicdataCL
  • Roadblocks and pitfalls• Lack of tool support for ontologydevelopment• Many tools for „mapping after the fact‟– Mapping should not be retrospective– Must be integrated into ontologydevelopment lifecycle• OWL Modeling pitfalls– Over-modeling– Under-modeling
  • Overcoming ontologydevelopment bottlenecks withTermGenie• Developed for GO– Instant compositional terms for curators– OWL axioms are added at time of termcreation• We are rolling out pheno-ontologyinstances– Trial run on FYPO and plant traitshttp://termgenie.org
  • Modeling confusion and analysisparalysis• 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
  • Modeling temporal progression• How did there come to be absence ofbeta cells in the pancreas?• What are the downstream effects?• Changes with ages– Hyperglycemic  hypoglycemic• Existing phenotype ontologies steerclear of causality– Next frontier
  • 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 foranalysis (see Damian‟s talk)• …a lot more
  • 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 ofcausality• Tools– CrossSpeciesPheno– Available:• GULO, TermGenie, OBO-Edit, Protégé 4, OWL Reasoners, Onto-Jenkins– Required: integration upstream
  • • 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 SmithAcknowledgments