Building an Interoperable Rare Disease Multi-omic Resource: The GREGoR Data Model and Dataset
A standardized data platform for rare disease research now connects over 12,000 participants across institutions, accelerating genetic diagnosis and discovery.
The GREGoR Consortium developed a scalable, modular data model for multi-omic rare disease data that has enabled analysis-ready harmonized datasets across distributed sites, covering 12,292 participants in 5,029 families. This infrastructure is being adopted by other rare disease consortia, with implications for accelerating genomic diagnosis and discovery in underdiagnosed conditions.
What the study was
- Study design
- Infrastructure/methods paper with prospective data model development
- Population
- 12,292 participants in 5,029 families with challenging rare disease cases across GREGoR Consortium sites
- Sample size
- 12292
- Category
- Genomics/Precision Medicine
- Maturity
- Exploratory
- Journal
- bioRxiv
Why it surfaced
Large-scale (n=12,292) rare disease multi-omic resource with interoperability framework; important infrastructure paper for rare disease genomics pipeline. Preprint cap: triage_score ≤7, evidence_maturity = Exploratory.
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