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GenEpiO: The Genomic Epidemiology Application Ontology for the 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. www.irida.ca1Simon 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
• No single existing ontology can adequately describe all the domains required for a genomic epidemiology
• Information sharing between jurisdictions is complex• Not all jurisdictions collect/store/report the same information• Fears of compromising investigations, IP concerns make Provinces “metadata sharing
risk averse”
Public Health Data Sharing and Information Flow in Canada
Mapping Genomic
Goal of IRIDA OntologyTo design and implement a genomic epidemiology application ontology suite to support the exchange and sharing of Public Health metadata and genomic sequence data.
Methods1. Interview users to model data flow 2. Resource reviews 3. Test application with real public health data
Results and Deliverables1. OWL File Encoding Required Metadata Elements
• GenEpiO combines different Epi, Lab, Genomics and Clinical data fields• Community contributions welcome. Contact: [email protected]
AcknowledgementsFunded by Genome Canada, Genome BC, the Genomics R&D Initiative (GRDI),
Cystic Fibrosis Canada and Compute Canada
3. Testing the IRIDA Ontology: Canada’s GRDI Pilot Project for Food and Water Safety
• Disease, age, sex, status of case, episode dates, episode identifier and geographic indicator shared between provinces and federal agencies
• For some diseases, there has been further agreement to provide an additional set of variables ("minimum data set”).
Provincial Epidemiology
National Microbiology Lab
Provincial Lab
Doctor Private or Hospital LabLHA
Patient
Local Public Health
Provincial Public Health
National Public Health
Federal Epidemiology
Genomics
Pathogen Taxonomy
SOPS
Diagnostic Test
Result Report
Laboratory-test centric
Clinical-patient centric
Epidemiology-case centric
Host Taxonomy
Symptoms
Demographics
Treatment
Vaccines
DrugsGeography
Public Health Intervention
Exposure
Contact
Food
Travel
Environment
Temporal Info
• Structured metadata is crucial for standardization, integration, querying and analysis i.e. to make sense of genomic data
Future Directions: Formation of Ontology Consortia
• FoodOn (Food Ontology) Consortium: https://github.com/FoodOntology
• GenEpiO (Genomic Epidemiology) Consortium: http://github.com/Public-Health-Bioinformatics/IRIDA_ontology
• Community contributions welcome. Contact: [email protected]
• GenEpiO implemented in “Metadata Manager” NCBI BioSample-compliant genome upload app, Timeline Line List visualizations
• Need for standardized Food, Antimicrobial Resistance, Surveillance, Result Reporting vocabulary
Line List visualizations based on GenEpiO fields: Timeline View
Genomic Epidemiology Ontology Will Help Integrate Genomics and Epidemiological Data
AcknowledgementsFunded by Genome Canada, Genome BC, the Genomics R&D Initiative (GRDI),
Cystic Fibrosis Canada and Compute Canada
2. Mapping Processes and Terms to Existing Ontologies
Bioinformaticians
