{"title":"代理面板使隐私意识外包的基因型插入","authors":"Degui Zhi, Xiaoqian Jiang, Arif O. Harmanci","doi":"10.1101/gr.278934.124","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"7 1","pages":""},"PeriodicalIF":6.2000,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Proxy panels enable privacy-aware outsourcing of genotype imputation\",\"authors\":\"Degui Zhi, Xiaoqian Jiang, Arif O. Harmanci\",\"doi\":\"10.1101/gr.278934.124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":12678,\"journal\":{\"name\":\"Genome research\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2025-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome research\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1101/gr.278934.124\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1101/gr.278934.124","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Proxy panels enable privacy-aware outsourcing of genotype imputation
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.
期刊介绍:
Launched in 1995, Genome Research is an international, continuously published, peer-reviewed journal that focuses on research that provides novel insights into the genome biology of all organisms, including advances in genomic medicine.
Among the topics considered by the journal are genome structure and function, comparative genomics, molecular evolution, genome-scale quantitative and population genetics, proteomics, epigenomics, and systems biology. The journal also features exciting gene discoveries and reports of cutting-edge computational biology and high-throughput methodologies.
New data in these areas are published as research papers, or methods and resource reports that provide novel information on technologies or tools that will be of interest to a broad readership. Complete data sets are presented electronically on the journal''s web site where appropriate. The journal also provides Reviews, Perspectives, and Insight/Outlook articles, which present commentary on the latest advances published both here and elsewhere, placing such progress in its broader biological context.