Achieving GWAS with homomorphic encryption

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Achieving GWAS with homomorphic encryption
Title:
Achieving GWAS with homomorphic encryption
Other Titles:
BMC Medical Genomics
Publication Date:
21 July 2020
Citation:
Sim, J. J., Chan, F. M., Chen, S., Meng Tan, B. H., & Mi Aung, K. M. (2020). Achieving GWAS with homomorphic encryption. BMC Medical Genomics, 13(S7). doi:10.1186/s12920-020-0717-y
Abstract:
Background: One way of investigating how genes affect human traits would be with a genome-wide association study (GWAS). Genetic markers, known as single-nucleotide polymorphism (SNP), are used in GWAS. This raises privacy and security concerns as these genetic markers can be used to identify individuals uniquely. This problem is further exacerbated by a large number of SNPs needed, which produce reliable results at a higher risk of compromising the privacy of participants. Methods: We describe a method using homomorphic encryption (HE) to perform GWAS in a secure and private setting. This work is based on a proposed algorithm. Our solution mainly involves homomorphically encrypted matrix operations and suitable approximations that adapts the semi-parallel GWAS algorithm for HE. We leverage upon the complex space of the CKKS encryption scheme to increase the number of SNPs that can be packed within a ciphertext. We have also developed a cache module that manages ciphertexts, reducing the memory footprint. Results: We have implemented our solution over two HE open source libraries, HEAAN and SEAL. Our best implementation took 24.70 minutes for a dataset with 245 samples, over 4 covariates and 10643 SNPs. Conclusions: We demonstrate that it is possible to achieve GWAS with homomorphic encryption with suitable approximations.
License type:
Attribution 4.0 International (CC BY 4.0)
Funding Info:
This research is supported by core funding from: Institute for Infocomm Research
Grant Reference no. :

This research / project is supported by the Agency for Science, Technology and Research - RIE2020 Advanced Manufacturing and Engineering (AME) Programmatic Program
Grant Reference no. : A19E3b0099
Description:
ISSN:
1755-8794
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