Ontologies for representing, integrating and analyzing                             phenotypes                             ...
Introduction   Motivation  MotivationRobert Hoehndorf (University of Cambridge)      Phenotype ontologies     21 June 2011...
Introduction   Motivation  MotivationRobert Hoehndorf (University of Cambridge)      Phenotype ontologies     21 June 2011...
Introduction     Ontology  Open Biomedical Ontologies (OBO)                                                     Individual...
Introduction   Ontology  Ontology  Phenotype and anatomy ontologies           anatomy ontologies: > 100,000 classes       ...
Introduction   Ontology  Ontology  Challenges for interoperability           “merely using ontologies [...] does not reduc...
Introduction   Ontology  Ontology  Example query        Find all regions in the human and mouse genome sequences that are ...
Phenotype ontology   Tetralogy of Fallot  Tetralogy of FallotRobert Hoehndorf (University of Cambridge)             Phenot...
Phenotype ontology   Tetralogy of Fallot  Tetralogy of Fallot  Human phenotypes           Overriding aorta (HP:0002623)   ...
Phenotype ontology   Tetralogy of Fallot  Tetralogy of Fallot  Phenotype description syntax   Overriding aorta (HP:0002623...
Phenotype ontology   Tetralogy of Fallot  Tetralogy of Fallot  Phenotype description syntax   Overriding aorta (HP:0002623...
Phenotype ontology   Tetralogy of Fallot  Tetralogy of Fallot  Phenotype description syntax   Overriding aorta (HP:0002623...
Phenotype ontology    Tetralogy of Fallot  Tetralogy of Fallot  UBERON human-mouse anatomy equivalences   Overriding aorta...
Phenotype ontology   Tetralogy of Fallot  Tetralogy of Fallot  Phenotype equivalence   Overriding aorta (MP:0000273):     ...
Phenotype ontology   Tetralogy of Fallot  Tetralogy of Fallot  Phenotype equivalence   Overriding aorta (MP:0000273):     ...
Phenotype ontology   Absence  Absence  Absent appendix   Absent appendix:           Q: lacks all parts of type (PATO:00020...
Phenotype ontology   Absence  Absence  Absent appendix   Absent appendix:           Q: lacks all parts of type (PATO:00020...
Phenotype ontology   Absence  Absence  Absent appendix   Absent appendix:           Q: lacks all parts of type (PATO:00020...
Phenotype ontology   Absence  Absence  Absent appendix   Absent appendix:           Q: lacks all parts of type (PATO:00020...
Phenotype ontology   Absence  Absence  Absent appendix           AbsentAppendix                    ∃pheneOf .(HumanBody   ...
Phenotype ontology   Absence  Absence  Absent appendix           Removal of conflicting axioms (has-part/part-of in anatomy...
Phenotype ontology   Absence  Ontology of phenotypes   Different formal expressions for phenotypes based on           quali...
Phenotype ontology   Discovering mouse models  Tetralogy of FallotRobert Hoehndorf (University of Cambridge)             P...
Phenotype ontology   Discovering mouse models  Phenotype alignments  Mouse model: Phc1Robert Hoehndorf (University of Camb...
Phenotype ontology   Discovering mouse models  Phenotype alignments  Tetralogy of Fallot: Phc1Robert Hoehndorf (University...
Knowledge representation   Modularization  Complexity of automated reasoning           ontologies based on OWL           O...
Knowledge representation   Modularization  Modularization           tractable subsets of OWL 2: EL, QL, RL           probl...
Knowledge representation   Modularization  Modularization           tractable subsets of OWL 2: EL, QL, RL           probl...
Knowledge representation   Modularization  Modularization           tractable subsets of OWL 2: EL, QL, RL           probl...
Knowledge representation   Modularization  Modularization  EL Vira   http://el-vira.googlecode.com           ontology modu...
Knowledge representation           Modularization  Modularization  EL Module            AbnormalityOfAppendix ≡           ...
Knowledge representation   Applications and evaluation  Phenotype alignments  PhenomeBLAST           apply to yeast, fly, w...
Knowledge representation   Applications and evaluation  Phenotype alignments  PhenomeBLASTRobert Hoehndorf (University of ...
Knowledge representation   Applications and evaluation  Phenotype alignments  PhenomeBLASTRobert Hoehndorf (University of ...
Knowledge representation   Applications and evaluation  Application  Comparison of phenotypes           direct comparison ...
Knowledge representation   Applications and evaluation  Application  Comparison of phenotypes   phenotype of mutations sub...
Knowledge representation   Applications and evaluation  Application  Similarity-based comparison           pairwise compar...
Knowledge representation       Applications and evaluation  Application  Similarity-based comparison: ROC                 ...
Knowledge representation   Applications and evaluation  Application  Similarity-based comparison: gene-disease association...
Knowledge representation   Applications and evaluation  Application  PhenomeBrowserRobert Hoehndorf (University of Cambrid...
Conclusions  Summary  Aspects of ontology-based information systems in biology           knowledge representation language...
Conclusions  Challenges and future research  Knowledge representation           establish reasoning infrastructure (OWLlin...
Conclusions  Challenges and future research  Ontology                                                     Individual      ...
Conclusions  Challenges and future research  Biology           add phenotype information                  20,000 knockout ...
Conclusions  Acknowledgements                                                                      John Gennari           ...
Conclusions   Thank you!Robert Hoehndorf (University of Cambridge)     Phenotype ontologies   21 June 2011   40 / 40
Upcoming SlideShare
Loading in …5
×

Ontologies for representing, integrating and analyzing phenotypes

875 views

Published on

The development and application of high-throughput technologies in biology leads to a rapid increase of data and knowledge and enables the possibility for a paradigm shift towards the personalized treatment of disease based on an individual patient’s genetic markup. Major challenges that biology faces today are to integrate data across different databases, domains, levels of granularity and species, and to make the information resulting from high-throughput experiments amenable to scientific analyses and the discovery of mechanisms underlying disease. In my talk, I will demonstrate how formal ontologies combined with recent progress in automated reasoning can be used to represent, integrate and analyze data resulting from high-throughput phenotyping experiments. I will show how an expressive formal representation of phenotype ontologies can lead to interoperability with biomedical ontologies of other domains, illustrate an ontology modularization approach that enables the use of automated reasoning over these ontologies and show how to integrate phenotype data across multiple species. Finally, I will demonstrate how measures of semantic similarity can be applied to analyze high-throughput phenotype data and reveal novel gene-disease associations and discuss how an ontology-based approach to the semantic integration of data in biomedicine can facilitate translational research and personalized medicine.

Published in: Technology, Education, Spiritual
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
875
On SlideShare
0
From Embeds
0
Number of Embeds
11
Actions
Shares
0
Downloads
19
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Ontologies for representing, integrating and analyzing phenotypes

  1. 1. Ontologies for representing, integrating and analyzing phenotypes Robert Hoehndorf Department of Genetics University of Cambridge 21 June 2011Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 1 / 40
  2. 2. Introduction Motivation MotivationRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 2 / 40
  3. 3. Introduction Motivation MotivationRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 3 / 40
  4. 4. Introduction Ontology Open Biomedical Ontologies (OBO) Individual Physical object Quality Function Process ChEBI Ontology Molecule Gene Sequence Ontology Transcript GO-CC Organelle Celltype Gene Ontology Cell Phenotype Tissue Ontology Organ Anatomy Ontology Body PopulationRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 4 / 40
  5. 5. Introduction Ontology Ontology Phenotype and anatomy ontologies anatomy ontologies: > 100,000 classes FMA, MA, WA, ZFA, FA, GO-CC, ... phenotype ontologies: > 20,000 classes HPO, MP, WBPhenotype, FBcv, APO, ... quality ontology: > 2,000 classes PATO process and function ontologies: > 25,000 classes Gene Ontology, ... alignments between anatomy ontologies UBERON, various mappingsRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 5 / 40
  6. 6. Introduction Ontology Ontology Challenges for interoperability “merely using ontologies [...] does not reduce heterogeneity: it just raises heterogeneity problems to a higher level” [Euzenat, 2007] implicit knowledge implicit semantics weakly formalized very largeRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 6 / 40
  7. 7. Introduction Ontology Ontology Example query Find all regions in the human and mouse genome sequences that are associated with Tetralogy of Fallot.Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 7 / 40
  8. 8. Phenotype ontology Tetralogy of Fallot Tetralogy of FallotRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 8 / 40
  9. 9. Phenotype ontology Tetralogy of Fallot Tetralogy of Fallot Human phenotypes Overriding aorta (HP:0002623) Ventricular septal defect (HP:0001629) Pulmonic stenosis (HP:0001642) Right ventricular hypertrophy (HP:0001667)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 9 / 40
  10. 10. Phenotype ontology Tetralogy of Fallot Tetralogy of Fallot Phenotype description syntax Overriding aorta (HP:0002623): Q: overlap with (PATO:0001590) E1: Aorta (FMA:3734) E2: Membranous part of interventricular septum (FMA:7135)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 10 / 40
  11. 11. Phenotype ontology Tetralogy of Fallot Tetralogy of Fallot Phenotype description syntax Overriding aorta (HP:0002623): Q: overlap with (PATO:0001590) E1: Aorta (FMA:3734) E2: Membranous part of interventricular septum (FMA:7135) HP:0002623 EquivalentTo: phene-of some (has-part some (FMA:3734 and has-quality some (PATO:0001590 and towards some FMA:7135)))Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 11 / 40
  12. 12. Phenotype ontology Tetralogy of Fallot Tetralogy of Fallot Phenotype description syntax Overriding aorta (HP:0002623): Q: overlap with (PATO:0001590) E1: Aorta (FMA:3734) E2: Membranous part of interventricular septum (FMA:7135) HP:0002623 EquivalentTo: phene-of some (has-part some (FMA:3734 and overlaps-with some FMA:7135))Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 12 / 40
  13. 13. Phenotype ontology Tetralogy of Fallot Tetralogy of Fallot UBERON human-mouse anatomy equivalences Overriding aorta (HP:0002623): Q: overlap with (PATO:0001590) E1: Aorta (FMA:3734) FMA:3734 EquivalentTo: MA:0000062 E2: Membranous part of interventricular septum (FMA:7135) FMA:7135 EquivalentTo: MA:0002939Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 13 / 40
  14. 14. Phenotype ontology Tetralogy of Fallot Tetralogy of Fallot Phenotype equivalence Overriding aorta (MP:0000273): Q: overlap with (PATO:0001590) E1: Aorta (MA:0000062) E2: Membranous interventricular septum (MA:0002939) MP:0000273 EquivalentTo: phene-of some (has-part some (MA:0000062 and has-quality some (PATO:0001590 and towards some MA:0002939)))Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 14 / 40
  15. 15. Phenotype ontology Tetralogy of Fallot Tetralogy of Fallot Phenotype equivalence Overriding aorta (MP:0000273): Q: overlap with (PATO:0001590) E1: Aorta (MA:0000062) E2: Membranous interventricular septum (MA:0002939) MP:0000273 EquivalentTo: phene-of some (has-part some (MA:0000062 and has-quality some (PATO:0001590 and towards some MA:0002939))) Consequence: MP:00000273 EquivalentTo: HP:0002623Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 14 / 40
  16. 16. Phenotype ontology Absence Absence Absent appendix Absent appendix: Q: lacks all parts of type (PATO:0002000) E1: Human body (FMA:20394) E2: Appendix (FMA:14542)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 15 / 40
  17. 17. Phenotype ontology Absence Absence Absent appendix Absent appendix: Q: lacks all parts of type (PATO:0002000) E1: Human body (FMA:20394) E2: Appendix (FMA:14542) AbsentAppendix ≡ LacksParts ∃towards.Appendix ∃inheresIn.HumanBody (Horrocks, 2007)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 15 / 40
  18. 18. Phenotype ontology Absence Absence Absent appendix Absent appendix: Q: lacks all parts of type (PATO:0002000) E1: Human body (FMA:20394) E2: Appendix (FMA:14542) AbsentAppendix ≡ LacksParts ∃towards.Appendix ∃inheresIn.HumanBody (Horrocks, 2007) AbsentAppendix ≡ LacksParts ∃towards.{Appendix} ∃inheresIn.HumanBody (Mungall, 2007)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 15 / 40
  19. 19. Phenotype ontology Absence Absence Absent appendix Absent appendix: Q: lacks all parts of type (PATO:0002000) E1: Human body (FMA:20394) E2: Appendix (FMA:14542) AbsentAppendix ≡ LacksParts ∃towards.Appendix ∃inheresIn.HumanBody (Horrocks, 2007) AbsentAppendix ≡ LacksParts ∃towards.{Appendix} ∃inheresIn.HumanBody (Mungall, 2007) AbsentAppendix ∃pheneOf .(HumanBody ¬∃hasPart.Appendix) (H et al., 2007, 2011)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 15 / 40
  20. 20. Phenotype ontology Absence Absence Absent appendix AbsentAppendix ∃pheneOf .(HumanBody ¬∃hasPart.Appendix) FMA: HumanBody ∃hasPart.Appendix HumanBody (John), AbsentAppendix(x), hasPhene(John, x)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 16 / 40
  21. 21. Phenotype ontology Absence Absence Absent appendix Removal of conflicting axioms (has-part/part-of in anatomy) Contextualize anatomy: Normal HumanBody ∃hasPart.(Normal Appendix) Use of non-monotonic reasoning: Normally: HumanBody ∃hasPart.Appendix Circumscription of ¬Normal Implementation in dlvhex IC-has-part(X,Y) :- ind(X),class(Y),inst(X,Z), CC-normally-has-part(Z,Y), not IC-lacks-has-part(X,Y), class(Z).Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 17 / 40
  22. 22. Phenotype ontology Absence Ontology of phenotypes Different formal expressions for phenotypes based on qualities, anatomical parts, functions, processes enable cross-species integration of phenotypes.Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 18 / 40
  23. 23. Phenotype ontology Discovering mouse models Tetralogy of FallotRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 19 / 40
  24. 24. Phenotype ontology Discovering mouse models Phenotype alignments Mouse model: Phc1Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 20 / 40
  25. 25. Phenotype ontology Discovering mouse models Phenotype alignments Tetralogy of Fallot: Phc1Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 21 / 40
  26. 26. Knowledge representation Modularization Complexity of automated reasoning ontologies based on OWL OWL 2 is based on description logic (SROIQ) satisfiability in SROIQ is 2NEXPTIME-completeRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 22 / 40
  27. 27. Knowledge representation Modularization Modularization tractable subsets of OWL 2: EL, QL, RL problem: identify a large (EL, QL, RL)-module of an OWL ontologyRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 23 / 40
  28. 28. Knowledge representation Modularization Modularization tractable subsets of OWL 2: EL, QL, RL problem: identify a large (EL, QL, RL)-module of an OWL ontology AbnormalityOfAppendix ≡ ∃pheneOf .(¬∃hasPart.(Normal Appendix)) ( EL) Z Z AbsentAppendix ≡ ∃pheneOf .(¬∃hasPart.Appendix) ( EL) Z ZRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 23 / 40
  29. 29. Knowledge representation Modularization Modularization tractable subsets of OWL 2: EL, QL, RL problem: identify a large (EL, QL, RL)-module of an OWL ontology AbnormalityOfAppendix ≡ ∃pheneOf .(¬∃hasPart.(Normal Appendix)) ( EL) Z Z AbsentAppendix ≡ ∃pheneOf .(¬∃hasPart.Appendix) ( EL) Z Z Inference: AbsentAppendix AbnormalityOfAppendix (EL)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 23 / 40
  30. 30. Knowledge representation Modularization Modularization EL Vira http://el-vira.googlecode.com ontology modularization retain signature of ontology identify EL, QL, RL axioms in deductive closure completeness is open problemRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 24 / 40
  31. 31. Knowledge representation Modularization Modularization EL Module AbnormalityOfAppendix ≡ ∃pheneOf .(¬∃hasPart.(Normal Appendix)) AbsentAppendix ≡ ∃pheneOf .(¬∃hasPart.Appendix) AbsentAppendix AbnormalityOfAppendix H et al., 2011. A common layer of interoperability for biomedical ontologies based on OWL EL. Bioinformatics, 27(7), 1001–1008.Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 25 / 40
  32. 32. Knowledge representation Applications and evaluation Phenotype alignments PhenomeBLAST apply to yeast, fly, worm, fish, mouse and human phenotypes phenotype alignment through OWL reasoning more than 300,000 classes and 1,000,000 axioms combination of HermiT (for modularization), CB and CEL reasoner classification time: 7 minutes http://phenomeblast.googlecode.orgRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 26 / 40
  33. 33. Knowledge representation Applications and evaluation Phenotype alignments PhenomeBLASTRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 27 / 40
  34. 34. Knowledge representation Applications and evaluation Phenotype alignments PhenomeBLASTRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 28 / 40
  35. 35. Knowledge representation Applications and evaluation Application Comparison of phenotypes direct comparison of phenotypes: disease phenotypes, e.g., tetralogy of Fallot phenotypes associated with genetic mutations (genotypes in mouse, fish, etc.)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 29 / 40
  36. 36. Knowledge representation Applications and evaluation Application Comparison of phenotypes phenotype of mutations subclass of disease phenotype allows inference of gene-disease association if disease phenotypes sufficient for having the disease mutation phenotypes necessary for having a specific genotypeRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 30 / 40
  37. 37. Knowledge representation Applications and evaluation Application Similarity-based comparison pairwise comparison of phenotypes semantic similarity: weighted Jaccard index result: similarity matrix between phenotypes (quantitative) evaluation based on predicting orthology, pathway, disease identify novel gene-disease associationsRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 31 / 40
  38. 38. Knowledge representation Applications and evaluation Application Similarity-based comparison: ROC 1 0.8 True positive rate 0.6 0.4 0.2 Disease Orthology Pathway 0 0 0.2 0.4 0.6 0.8 1 False positive rateRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 32 / 40
  39. 39. Knowledge representation Applications and evaluation Application Similarity-based comparison: gene-disease associations Adam19 and Fgf15 genes in mice may be involved in Tetralogy of Fallot Aberrant pathways Cytokine-cytokine receptor interaction pathway (ko04060) is significantly correlated with Tetralogy of Fallot (p = 5 · 10−7 , Wilcoxon signed-rank test) Gene disease associations for orphan diseases Slc34a1 (MGI:1345284) and Fanconi renotubular syndrome 1 (OMIM:134600)Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 33 / 40
  40. 40. Knowledge representation Applications and evaluation Application PhenomeBrowserRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 34 / 40
  41. 41. Conclusions Summary Aspects of ontology-based information systems in biology knowledge representation language expressiveness non-monotonicity complexity of inferences ontological decisions anatomy (parthood, connectedness) physiology (function) pathology, disease (normality, abnormality) statistical/similarity-based framework semantic similarity account for incomplete information account for noisy dataRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 35 / 40
  42. 42. Conclusions Challenges and future research Knowledge representation establish reasoning infrastructure (OWLlink, ...) improve reasoning performance (OWL profiles, modularity, approximate reasoning) OWL reasoning with prototypes, non-monotonic reasoning, abduction explore alternatives to OWLRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 36 / 40
  43. 43. Conclusions Challenges and future research Ontology Individual Physical object Quality Function Process ChEBI Ontology Molecule Gene Sequence Ontology Transcript GO-CC Organelle Celltype Gene Ontology Cell Phenotype Tissue Ontology Organ Anatomy Ontology Body PopulationRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 37 / 40
  44. 44. Conclusions Challenges and future research Biology add phenotype information 20,000 knockout mice dog, rat, slime mold, ... define disease phenotypes extension to other domains functional genomics pharmacology, drug discovery systems biology clinical research, decision support quantifiable evaluationRobert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 38 / 40
  45. 45. Conclusions Acknowledgements John Gennari George Gkoutos Pierre Grenon Heinrich Herre Pascal Hitzler Janet Kelso Frank Loebe Michel Dumontier Anika Oellrich Dietrich Kay Pruefer Rebholz-Schuhmann Paul Schofield Nico Adams Stefan Schulz Dan Cook Robert Stevens Bernard de Bono Sarala Wimalaratne ...Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 39 / 40
  46. 46. Conclusions Thank you!Robert Hoehndorf (University of Cambridge) Phenotype ontologies 21 June 2011 40 / 40

×