RT Journal Article
SR Electronic
T1 Privacy-Preserving Genotype Imputation in a Trusted Execution Environment
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.02.02.429428
DO 10.1101/2021.02.02.429428
A1 Natnatee Dokmai
A1 Can Kockan
A1 Kaiyuan Zhu
A1 XiaoFeng Wang
A1 S. Cenk Sahinalp
A1 Hyunghoon Cho
YR 2021
UL http://biorxiv.org/content/early/2021/02/03/2021.02.02.429428.abstract
AB Genotype imputation is an essential tool in genetics research, whereby missing genotypes are inferred based on a panel of reference genomes to enhance the power of downstream analyses. Recently, public imputation servers have been developed to allow researchers to leverage increasingly large-scale and diverse genetic data repositories for imputation. However, privacy concerns associated with uploading one’s genetic data to a third-party server greatly limit the utility of these services. In this paper, we introduce a practical, secure hardware-based solution for a privacy-preserving imputation service, which keeps the input genomes private from the service provider by processing the data only within a Trusted Execution Environment (TEE) offered by the Intel SGX technology. Our solution features SMac, an efficient, side-channel-resilient imputation algorithm designed for Intel SGX, which employs the hidden Markov model (HMM)-based imputation strategy also utilized by a state-of-the-art imputation software Minimac. SMac achieves imputation accuracies virtually identical to those of Minimac and provides protection against known attacks on SGX while maintaining scalability to large datasets. We additionally show the necessity of our strategies for mitigating side-channel risks by identifying vulnerabilities in existing imputation software and controlling their information exposure. Overall, our work provides a guideline for practical and secure implementation of genetic analysis tools in SGX, representing a step toward privacy-preserving analysis services that can facilitate data sharing and accelerate genetics research.†Availability Our software is available at https://github.com/ndokmai/sgx-genotype-imputation.Competing Interest StatementThe authors have declared no competing interest.