One of the major challenges in genomic data sharing is protecting participants' privacy in collaborative studies and when genomic data is outsourced to perform analysis tasks, e.g., 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 while 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. While 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.

Download full-text PDF

Source
http://dx.doi.org/10.1101/gr.278934.124DOI Listing

Publication Analysis

Top Keywords

proxy panels
12
genotype imputation
12
outsourcing genotype
8
genomic data
8
imputation
7
panels
6
panels enable
4
enable privacy-aware
4
privacy-aware outsourcing
4
genotype
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!