Secure and federated genome-wide association studies for biobank-scale datasets.

ABSTRACT: Sharing data across institutions for genome-wide association studies (GWAS) would enhance the discovery of genetic variation linked to health and disease^1,2. However, existing data-sharing regulations limit the scope of such collaborations³. Although cryptographic tools for secure computation promise to enable collaborative analysis with formal privacy guarantees, existing approaches either are computationally impractical or do not implement current state-of-the-art methods^4-6. We introduce secure federated genome-wide association studies (SF-GWAS), a combination of secure computation frameworks and distributed algorithms that empowers efficient and accurate GWAS on private data held by multiple entities while ensuring data confidentiality. SF-GWAS supports

SUBMITTER: Cho H 

PROVIDER: S-EPMC11985345 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature