Secure and federated quantitative trait loci mapping with privateQTL.

ABSTRACT: Understanding the relationship between genotypes and phenotypes is crucial for advancing personalized medicine. Expression quantitative trait loci (eQTL) mapping plays a significant role by correlating genetic variants to gene expression levels. Despite the progress made by large-scale projects, eQTL mapping still faces challenges in statistical power and privacy concerns. Multi-site studies can increase sample sizes but are hindered by privacy issues. We present privateQTL, a novel framework leveraging secure multi-party computation for secure and federated eQTL mapping. When tested in a real-world scenario with data from different studies, privateQTL outperformed meta-analysis by accurately correcting for covariates and batch effect and retaining higher accuracy and precision for both eG

SUBMITTER: Choi YA 

PROVIDER: S-EPMC11872535 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature