Title
Privacy-preserving Approximate GWAS computation based on Homomorphic Encryption.
Abstract
Background One of three tasks in a secure genome analysis competition called iDASH 2018 was to develop a solution for privacy-preserving GWAS computation based on homomorphic encryption. The scenario is that a data holder encrypts a number of individual records, each of which consists of several phenotype and genotype data, and provide the encrypted data to an untrusted server. Then, the server performs a GWAS algorithm based on homomorphic encryption without the decryption key and outputs the result in encrypted state so that there is no information leakage on the sensitive data to the server. Methods We develop a privacy-preserving semi-parallel GWAS algorithm by applying an approximate homomorphic encryption scheme HEAAN. Fisher scoring and semi-parallel GWAS algorithms are modified to be efficiently computed over homomorphically encrypted data with several optimization methodologies; substitute matrix inversion by an adjoint matrix, avoid computing a superfluous matrix of super-large size, and transform the algorithm into an approximate version. Results Our modified semi-parallel GWAS algorithm based on homomorphic encryption which achieves 128-bit security takes 30-40 minutes for 245 samples containing 10,000-15,000 SNPs. Compared to the truep-value from the original semi-parallel GWAS algorithm, theF(1)score of ourp-value result is over 0.99. Conclusions Privacy-preserving semi-parallel GWAS computation can be efficiently done based on homomorphic encryption with sufficiently high accuracy compared to the semi-parallel GWAS computation in unencrypted state.
Year
DOI
Venue
2019
10.1186/s12920-020-0722-1
BMC MEDICAL GENOMICS
Keywords
Field
DocType
Homomorphic encryption,Privacy,GWAS,Fisher scoring
Homomorphic encryption,Computer science,Theoretical computer science,Computation
Journal
Volume
Issue
ISSN
13
SUPnan
1755-8794
Citations 
PageRank 
References 
1
0.35
0
Authors
6
Name
Order
Citations
PageRank
Duhyeong Kim1131.90
Yongha Son242.13
Dongwoo Kim3145.12
Andrey Kim4745.70
Seungwan Hong5124.70
Jung Hee Cheon61787129.74