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Integrating clinical and model
organism genotype-phenotype data
for improved disease discovery
Melissa Haendel
ClinGen/DEC...
There are 47,964 variants of
unknown significance in
ClinVar
What are we gonna do about
that?
The Human Phenotype Ontology
Each disease is associated with different phenotype nodes in the graph
Disease or Patient
HPO concepts are not well
represented in other vocabularies
Winnenburg and Bodenreider, ISMB PhenoDay, 2014
UMLS
SNOMED CT...
Phenotype “Blast”: Which phenotypic
profile is graphically most similar?
Disease X
Patient
Disease Y
Finding the phenotype graph in
common
Disease X
Patient
Disease Y
The Human Phenotype Ontology
Hyposmia
Abnormality of
globe location
eyeball of
camera-type eye
sensory
perception of smell...
Why we need all the organisms
Clinicians and researchers speak
different languages
Diversity of disease and
phenotype vocabularies
Using semantics to bridge
vocabularies
Using semantics to bridge
vocabularies
Standardizing Cross-species G2P
Data + Ontologies
 SciGraph: A Neo4j-backed ontology store
 All species ontologies and G...
Combining genotype and
phenotype data for variant prioritization
Whole exome
Remove off-target and
common variants
Variant...
Cross-species phenotypic profile
comparison for disease discovery
Visualizing phenotypic similarity
http://monarchinitiative.org/page/phenogrid
AcknowledgmentsOHSU
Nicole Vasilesky
Matt Brush
Bryan Laraway
Shahim Essaid
Kent Shefchek
NIH-UDP
William Bone
Murat Sinca...
If you use Monarch
ontologies or tools,
please attribute us!
Please send feedback
too, don’t let it be a one
way street.
Extra
Propagating phenotypes across
genotypic levels
We learn different things from
different organisms
Monarch in the GA4GH
MatchMaker Exchange
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Integrating clinical and model organism G2P data for disease discovery

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Presented at the ClinGen meeting in DC May 28, 2015

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Integrating clinical and model organism G2P data for disease discovery

  1. 1. Integrating clinical and model organism genotype-phenotype data for improved disease discovery Melissa Haendel ClinGen/DECIPHER meeting 2015.05.28 @monarchinit www.monarchinitiative.org @ontowonka
  2. 2. There are 47,964 variants of unknown significance in ClinVar What are we gonna do about that?
  3. 3. The Human Phenotype Ontology Each disease is associated with different phenotype nodes in the graph Disease or Patient
  4. 4. HPO concepts are not well represented in other vocabularies Winnenburg and Bodenreider, ISMB PhenoDay, 2014 UMLS SNOMED CT CHV MedDRA MeSH NCIT ICD10-C ICD9-CM ICD-10 OMIM MedlinePlus
  5. 5. Phenotype “Blast”: Which phenotypic profile is graphically most similar? Disease X Patient Disease Y
  6. 6. Finding the phenotype graph in common Disease X Patient Disease Y
  7. 7. The Human Phenotype Ontology Hyposmia Abnormality of globe location eyeball of camera-type eye sensory perception of smell Abnormal eye morphology Motor neuron atrophyDeeply set eyes motor neuronCL 34571 annotations in 22 species 157534 phenotype annotations 2150 phenotype annotations
  8. 8. Why we need all the organisms
  9. 9. Clinicians and researchers speak different languages
  10. 10. Diversity of disease and phenotype vocabularies
  11. 11. Using semantics to bridge vocabularies
  12. 12. Using semantics to bridge vocabularies
  13. 13. Standardizing Cross-species G2P Data + Ontologies  SciGraph: A Neo4j-backed ontology store  All species ontologies and G2P data can be stored in a graph together  Advantages: Semantics + Speed + Flexibility  Propagate provenance and evidence  Using to develop and evaluate GA4GH G2P schemas https://github.com/SciGraph/SciGraph
  14. 14. Combining genotype and phenotype data for variant prioritization Whole exome Remove off-target and common variants Variant score from allele freq and pathogenicity Phenotype score from phenotypic similarity PHIVE score to give final candidates https://www.sanger.ac.uk/resources/databases/exom iser/query/exomiser2 Mendelian filters
  15. 15. Cross-species phenotypic profile comparison for disease discovery
  16. 16. Visualizing phenotypic similarity http://monarchinitiative.org/page/phenogrid
  17. 17. AcknowledgmentsOHSU Nicole Vasilesky Matt Brush Bryan Laraway Shahim Essaid Kent Shefchek NIH-UDP William Bone Murat Sincan David Adams Joie Davis Neal Boerkoel Cyndi Tifft Bill Gahl UDN Alexa McCray Rachel Ramoni Garvan Tudor Groza Lawrence Berkeley Nicole Washington Suzanna Lewis Jeremy Xuan Chris Mungall UCSD Jeff Grethe Chris Condit Maryann Martone U of Pitt Chuck Borromeo Vincent Agresti Harry Hochheiser Sanger Anika Oehlrich Jules Jacobson Damian Smedley Charité Sebastian Kohler Sandra Doelken Sebastian Bauer Peter Robinson Toronto Marta Girdea Sergiu Dumitriu Heather Trang Bailey Gallinger Orion Buske Mike Brudno JAX Cynthia Smith Current Funding: NIH Office of Director: 1R24OD011883 HHSN268201300036C, HHSN268201400093P
  18. 18. If you use Monarch ontologies or tools, please attribute us! Please send feedback too, don’t let it be a one way street.
  19. 19. Extra
  20. 20. Propagating phenotypes across genotypic levels
  21. 21. We learn different things from different organisms
  22. 22. Monarch in the GA4GH MatchMaker Exchange

Presented at the ClinGen meeting in DC May 28, 2015

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