Secure genome-wide association analysis using multiparty computation.

ABSTRACT: Most sequenced genomes are currently stored in strict access-controlled repositories. Free access to these data could improve the power of genome-wide association studies (GWAS) to identify disease-causing genetic variants and aid the discovery of new drug targets. However, concerns over genetic data privacy may deter individuals from contributing their genomes to scientific studies and could prevent researchers from sharing data with the scientific community. Although cryptographic techniques for secure data analysis exist, none scales to computationally intensive analyses, such as GWAS. Here we describe a protocol for large-scale genome-wide analysis that facilitates quality control and population stratification correction in 9K, 13K, and 23K individuals while maintaining the confidentia

SUBMITTER: Cho H 

PROVIDER: S-EPMC5990440 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature