Identifying disease-causing mutations with privacy protection.

ABSTRACT:

Motivation

The use of genome data for diagnosis and treatment is becoming increasingly common. Researchers need access to as many genomes as possible to interpret the patient genome, to obtain some statistical patterns and to reveal disease-gene relationships. The sensitive information contained in the genome data and the high risk of re-identification increase the privacy and security concerns associated with sharing such data. In this article, we present an approach to identify disease-associated variants and genes while ensuring patient privacy. The proposed method uses secure multi-party computation to find disease-causing mutations under specific inheritance models without sacrificing the privacy of individuals. It discloses only variants or genes obtained as a result of the a

SUBMITTER: Akgun M 

PROVIDER: S-EPMC7850099 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature