NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #41

Abstract Summary The NIH’s database of Genotypes and Phenotypes (dbGaP) includes data from 3,000+ studies across 800 diseases/focuses, involving 4 million participants and 450,000+ phenotype variables. dbGaP has supported over 8,000 publications. As researchers increasingly rely on cloud platforms to conduct cross-study analysis, both interoperability and ease of access are urgently needed. We developed FHIR (Fast Healthcare Interoperability Resources) API for dbGaP to deliver both open-access and controlled-access dbGaP data via FHIR. The open-access API provides programmatic access to study metadata, enabling researchers to discover relevant datasets for data discovery. Controlled-access API deliver over 1.1 billion phenotypic observations and molecular sequence files through persistent URLs using the GA4GH Data Repository Service (DRS), another global standard. We will show how a simple Python script in a Jupyter notebook can perform phenotype-driven statistical analysis across multiple datasets and repositories using the FHIR API. This approach enhances data reuse, facilitates cohort building, and helps accelerate reproducible research at scale.