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Sponsor Details

Poster Number
17
Poster Title
Federated Discovery of Rare Disease Genomic Data Through GA4GH Beacon v2: Integrating CQDG into the PCGL Network
Authors
David A.L. Morais 1, Jean-Philippe Thibert 1, David Bujold 2, Guillaume Bourque 2, Vincent Ferretti 1, PCGL 3

1.CHU Sainte-Justine Research Centre, Montreal Canada
2.Canadian Centre for Computational Genomics, Montreal Canada
3.The Pan-Canadian Genome Library Project Team
Abstract
Centralized genomic data infrastructures in Canada face significant challenges, including high operational costs, interprovincial legal constraints, and technical barriers to scalability. These limitations underscore the importance of federated approaches that preserve local governance while enabling secure, national data discovery.
The Quebec Centre for Genomic Data (CQDG) is a general-purpose genomic data commons supporting studies ranging from population cohorts to rare diseases and cancer. Built on Secure Data for Health (SD4H) cloud infrastructure, CQDG hosts over 20,000 participant genomes and exomes, integrates data from Quebec’s healthcare system, and supports interoperability through standards like FHIR (Fast Healthcare Interoperability Resources) and GA4GH DUO.
The Pan-Canadian Genome Library (PCGL) provides a federated architecture for archiving and responsible access to Canadian human genomic data. PCGL implements GA4GH Beacon v2 to enable secure, metadata-based discovery across distributed datasets while respecting jurisdictional and ethical boundaries.
We present the integration of CQDG as the first federated node in the PCGL Beacon v2 network. This allows users to query CQDG data from the PCGL interface using phenotypic and clinical filters defined in the phenopacket model, while maintaining local access control through project-specific DACOs (Data Access and Compliance Office) and DUO tagging.
This integration demonstrates a scalable model for federated data discovery across Canadian genomic initiatives. As additional datasets join the PCGL Beacon v2 network, this architecture enables harmonized querying, increased cohort sizes for rare disease and cancer research, and standardized metadata interoperability. It also promotes consistent implementation of access policies and supports long-term sustainability of Canadian genomic data resources.
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