ArticleCell systems2021
Ultrafast homomorphic encryption models enable secure outsourcing of genotype imputation.
Article in Cell systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- A simple demonstration of a privacy-preserving de-centralised genotype imputation workflow.PloS one · 2026Article
- NitroGene: privacy-preserving collaborative genomic analysis using AWS nitro enclaves.Bioinformatics advances · 2026Article
- Revolutionizing gastrointestinal cancer research with artificial intelligence: From precision patient stratification to real-world evidence.World journal of gastrointestinal oncology · 2025Review
- PRISM: privacy-preserving rare disease analysis using fully homomorphic encryption.Bioinformatics (Oxford, England) · 2025Article
- Article
- Toward owner governance in genomic data privacy with Governome.Cell reports methods · 2025Article
- SURFBAT: a surrogate family based association test building on large imputation reference panels.G3 (Bethesda, Md.) · 2025Article
- Secure and scalable gene expression quantification with pQuant.Nature communications · 2025Article
- Proxy panels enable privacy-aware outsourcing of genotype imputation.Genome research · 2025Article
- Genomic privacy and security in the era of artificial intelligence and quantum computing.Discover computing · 2025Review
- Privacy-Enhancing Technologies in Biomedical Data Science.Annual review of biomedical data science · 2024Review
- Privacy-preserving model evaluation for logistic and linear regression using homomorphically encrypted genotype data.Journal of biomedical informatics · 2024Article
- Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision.Briefings in bioinformatics · 2024Review
- Legal aspects of privacy-enhancing technologies in genome-wide association studies and their impact on performance and feasibility.Genome biology · 2024Review
- A resampling-based approach to share reference panels.Nature computational science · 2024Article
- Searching across-cohort relatives in 54,092 GWAS samples via encrypted genotype regression.PLoS genetics · 2024Article
- Federated Analysis for Privacy-Preserving Data Sharing: A Technical and Legal Primer.Annual review of genomics and human genetics · 2023Review
- Federated generalized linear mixed models for collaborative genome-wide association studies.iScience · 2023Article
- PP-DDP: a privacy-preserving outsourcing framework for solving the double digest problem.BMC bioinformatics · 2023Article
- Privacy-preserving cancer type prediction with homomorphic encryption.Scientific reports · 2023Article
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21 authors.
Funding
Abstract
Genotype imputation is a fundamental step in genomic data analysis, where missing variant genotypes are predicted using the existing genotypes of nearby "tag" variants. Although researchers can outsource genotype imputation, privacy concerns may prohibit genetic data sharing with an untrusted imputation service. Here, we developed secure genotype imputation using efficient homomorphic encryption (HE) techniques. In HE-based methods, the genotype data are secure while it is in transit, at rest, and in analysis. It can only be decrypted by the owner. We compared secure imputation with three state-of-the-art non-secure methods and found that HE-based methods provide genetic data security with comparable accuracy for common variants. HE-based methods have time and memory requirements that are comparable or lower than those for the non-secure methods. Our results provide evidence that HE-based methods can practically perform resource-intensive computations for high-throughput genetic data analysis. The source code is freely available for download at https://github.com/K-miran/secure-imputation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.