Proxy Panels Enable Privacy-Aware Outsourcing of Genotype Imputation

Authors

Degui Zhi
Xiaoqian Jiang
Arif Harmanci

Publication Date

2-14-2025

Journal

Genome Research

Abstract

One of the major challenges in genomic data sharing is protecting participants' privacy in collaborative studies and in cases when genomic data are outsourced to perform analysis tasks, for example, genotype imputation services and federated collaborations genomic analysis. Although numerous cryptographic methods have been developed, these methods may not yet be practical for population-scale tasks in terms of computational requirements, rely on high-level expertise in security, and require each algorithm to be implemented from scratch. In this study, we focus on outsourcing of genotype imputation, a fundamental task that utilizes population-level reference panels, and develop protocols that rely on using "proxy panels" to protect genotype panels, whereas the imputation task is being outsourced at servers. The proxy panels are generated through a series of protection mechanisms such as haplotype sampling, allele hashing, and coordinate anonymization to protect the underlying sensitive panel's genetic variant coordinates, genetic maps, and chromosome-wide haplotypes. Although the resulting proxy panels are almost distinct from the sensitive panels, they are valid panels that can be used as input to imputation methods such as Beagle. We demonstrate that proxy-based imputation protects against well-known attacks with a minor decrease in imputation accuracy for variants in a wide range of allele frequencies.

Keywords

Humans, Outsourced Services, Genotype, Algorithms, Genetic Privacy, Haplotypes, Genomics, Polymorphism, Single Nucleotide, Information Dissemination

DOI

10.1101/gr.278934.124

PMID

39794122

PMCID

PMC11874966

PubMedCentral® Posted Date

2-1-2025

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes