Secure discovery of genetic relatives across large-scale and distributed genomic data sets.

ABSTRACT: Finding relatives within a study cohort is a necessary step in many genomic studies. However, when the cohort is distributed across multiple entities subject to data-sharing restrictions, performing this step often becomes infeasible. Developing a privacy-preserving solution for this task is challenging owing to the burden of estimating kinship between all the pairs of individuals across data sets. We introduce SF-Relate, a practical and secure federated algorithm for identifying genetic relatives across data silos. SF-Relate vastly reduces the number of individual pairs to compare while maintaining accurate detection through a novel locality-sensitive hashing (LSH) approach. We assign individuals who are likely to be related together into buckets and then test relationships only between i

SUBMITTER: Hong MM 

PROVIDER: S-EPMC11529841 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature