GenEpiO: The Genomic Epidemiology Application Ontology for the Standardization and Integration of Microbial Genomic, Clinical and Epidemiological Data

1. GenEpiO: The Genomic Epidemiology Application
Ontology for the Standardization and Integration of Microbial
Genomic, Clinical and Epidemiological Data
Emma 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.ca
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
• 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 Ontology
To design and implement a genomic epidemiology application
ontology suite to support the exchange and sharing of Public Health
metadata and genomic sequence data.
Methods
1. 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
• Community contributions welcome. Contact: ontology-group-irida@googlegroups.com
Acknowledgements
Funded 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 Lab
LHA
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
Drugs
Geography
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:
ontology-group-irida@googlegroups.com
• 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
Acknowledgements
Funded 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