1. Integrating phenotype ontologies across multiple speciesCaltech 2009 Chris Mungall

2. Conservation of phenotypes

3. How do we compare phenotypes across species? Multiple project or species specific phenotype ontologies MP: mouse HP: human WP: worm TO: plant APO: fungi Data is not comparable How do we know they are built according to the same principles?

4. Anatomical and structural entities in OBO

7. Examples

8. Relational Qualities Have a bearer - have an additional dependency on some type of entity

9. EQ expressions can be written in obo format Why? Formal semantics Edit within OBO-Edit as genus-differentia definitions Use the OBO-Edit reasoner Can also be translated to OWL

10. EQ expressions can be written in obo format Why? Formal semantics Edit within OBO-Edit as genus-differentia definitions Use the OBO-Edit reasoner Can also be translated to OWL

11. EQ expressions can be written in obo format

12. EQ vs dedicated phenotype ontology Some groups pre-compose phenotype descriptions terms generated in advance by ontology editor ontology editors adds defs etc dedicated phenotype ontology often species-specific Other groups post-compose phenotype descriptions descriptions composed as needed by annotators no dedicated phenotype ontology

13. Methodologies

14. Unifying descriptions Equivalence Mappings between term EQ expression

15. Methods Use obol to generate first pass and updates parses term name assumes semi-controlled syntax Manually edit obo xp file

16. Results

17. Advantages Reuse PATO across ontologies Make sure we’re saying the same thing We can use the OBO-Edit reasoner to compute the is_a hierarchy We can enhance queries within species. E.g. find all genes that have a phenotype affecting sperm (CL:0000019 / WBbt:0006798) We can compare across species

18. Reasoning

19. Reasoner Results: HP/MP

20. Comparing across species Requirements: Phenotype ontology mappings Mappings between anatomy ontologies Uberon Multi-species anatomy ontology No assumption of homology Analogy is useful to; e.g. eyes Scope: metazoans Applicability outside vertebrates controversial Better to focus on cells (CL)

21. Mapping AOs to Uberon

22. Phenoblast: Quantifying similarity SimJ: 0.42 MaxIC: 13.4 SimJ: 0.17 MaxIC: 6.2 SimJ: 0.32 MaxIC: 12.1

23. Recovering pathway members by phenotypic similarity

24. Conclusions Sharing ontologies is good PATO / EQs can be used to help build ontologies as well as in annotation Find mistakes Automatically build DAG (reasoning) Mapping a phenotype ontology to EQs gives you the best of both worlds Control over the terms used in annotation Comparing data across species Where anatomical similarities permit..