Genotype Imputation with Homomorphic Encryption

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Genotype Imputation with Homomorphic Encryption
Title:
Genotype Imputation with Homomorphic Encryption
Journal Title:
2021 6th International Conference on Biomedical Signal and Image Processing
Keywords:
Publication Date:
08 November 2021
Citation:
Chan, F. M., Badawi, A. Q. A. A., Sim, J. J., Tan, B. H. M., Sheng, F. C., & Aung, K. M. M. (2021). Genotype Imputation with Homomorphic Encryption. 2021 6th International Conference on Biomedical Signal and Image Processing. doi:10.1145/3484424.3484426
Abstract:
Genotype imputation is a technique used to determine unobserved genomic markers when sequencing genomic data. This is a cost effective method for sequencing a genome. Due to the large amount of personal identifiable information involved in genomic imputation, there is a rising concern for analysis of such nature to be secure and private. We describe a method using homomorphic encryption (HE) to perform genotype imputation in a secure and private setting. Our solution first involves training a logistic regression model and performing the imputation in the encrypted domain. We have implemented our solution over using the open sourced Homomorphic Encryption library, SEAL. We are able to impute 500 SNPs within 5 minutes, with an accuracy of 97.3%.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - RIE2020 Advanced Manufacturing and Engineering (AME) Programmatic Program
Grant Reference no. : A19E3b0099
Description:
© Author | ACM. 2021 This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in 2021 6th International Conference on Biomedical Signal and Image Processing, http://dx.doi.org/10.1145/3484424.3484426
ISBN:
9781450390507
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