Emma Griffiths ASM microbe gen_epio_poster
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Transcript of Emma Griffiths ASM microbe gen_epio_poster
GenEpiO: The Genomic Epidemiology Application Ontology for Standardization and Integration of Microbial
Genomic, Clinical and Epidemiological DataEmma Griffiths1, Damion Dooley2, Mélanie Courtot3, Josh Adam4, Franklin Bristow4, João A Carriço5, Bhavjinder K. Dhillon1, Alex Keddy6, Matthew Laird3, Thomas Matthews4, Aaron Petkau4, Julie Shay1, Geoff Winsor1, the IRIDA Ontology Advisory Group7, Robert Beiko6, Lynn M Schriml8, Eduardo Taboada9, Gary Van Domselaar4, Morag Graham4, Fiona Brinkman1 and William Hsiao2.1Simon Fraser University, Greater Vancouver, BC, Canada; 2 BC Public Health Microbiology and Reference Laboratory, Vancouver, BC, Canada; 3 European Bioinformatics Institute, Hinxton, Cambridge, UK; 4National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada; 5Faculty of Medicine, University of Lisbon, Lisbon, Portugal; 6Dalhousie University, Halifax, NS, Canada; 7BC Centre for Disease Control, Vancouver, BC, Canada; 8University of Maryland School of Medicine, Baltimore, MD, USA; 9National Microbiology Laboratory, Public Health Agency of Canada, Lethbridge, AB, Canada
Background• Whole genome sequencing (WGS) provides high resolution
microbial pathogen typing for foodborne outbreak investigation
Mapping Genomic
Methods1. Interview users to model data flow 2. Resource reviews 3. Test application with real public health data
Results and Deliverables
1. OWL File Encoding Required Metadata Elements • GenEpiO combines different Epi, Lab, Genomics and Clinical data fields• Terms organized into hierarchies• Logical relationships being developed• Community contributions welcome. Contact: [email protected]
• Structured metadata is crucial for standardization, integration, querying and analysis i.e. to make sense of genomic data
Genomic Epidemiology Ontology Will Help Integrate Genomics and Epidemiological Data
Bioinformaticians
Mapping GenomicFuture Directions: Formation of International Ontology Consortia
• FoodOn (Food Ontology) Consortium: https://github.com/FoodOntology
• GenEpiO (Genomic Epidemiology) Consortium http://github.com/Public-Health-Bioinformatics/IRIDA_ontology
AcknowledgementsFunded by Genome Canada, Genome BC, the Genomics R&D Initiative (GRDI), Cystic Fibrosis Canada and Compute Canada,
with the support of AllerGen NCE Inc.
www.fda.gov
4. Testing the IRIDA Ontology: Canada’s GRDI Pilot Project for Food and Water Safety
• GenEpiO implemented in “Metadata Manager” NCBI BioSample-compliant genome upload form
Line List visualizations based on GenEpiO fields: Timeline View
3. Implementing GenEpiO: IRIDA Visualizations
Poster Number: 297Presentation: Mon June 20
Simon Fraser University(778)[email protected]
2. Mapping Processes and Terms to Existing Ontologies
Genomics
Pathogen Taxonomy
SOPSDiagnostic
TestsResult
Reports
LaboratoryTest
centric
Clinical-Patient centric
EpidemiologyCase centric
Host Taxonomy
Symptoms
Demographics
Treatment
Vaccines
DrugsGeography
Public Health
Intervention
Exposure
Contact
Food
Travel
EnvironmentTemporal
Info
Improved Public Health
Investigation power!
A Genomic Epidemiology Ontology has Advantages for Public Health.
1. Eliminates semantic ambiguity2. Term-mapping allows customization3. Faster data integration4. Triggers actionable events in same way5. Reproducibility (accreditation, validation)
• No single existing ontology can adequately describe all the domains required for a genomic epidemiology
Goal of Genomic Epidemiology Application Ontology (GenEpiO)
To design and implement a genomic epidemiology application ontology to support the exchange and sharing of Public Health metadata and genomic sequence data.
• HIPAA patient privacy fields flagged
• Need for better: Food, Antimicrobial Resistance, Surveillance, Result Reporting vocabulary
• Standardized, well-defined hierarchy terms • interconnected with logical relationships• “knowledge-generation engine”
Ontologies Standardize Vocabulary and Enable Complex Querying.
Resolves issues: • Synonyms • Taxonomy • Granularity • Specificity
Join us!
See draft version at https://github.com/GenEpiO/genepio
www.irida.ca
Example Food Hierarchies
A)
B)