Reconstruction of private genomes through reference-based genotype imputation.
Reconstruction of private genomes through reference-based genotype imputation.
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DOI：
10.1186/s13059-023-03105-6
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发表时间：
2023-12-06
期刊：
影响因子：
12.3
通讯作者：
中科院分区：
文献类型：
--
作者：
基因型插补是遗传学研究中提高数据质量和统计能力的重要步骤。公共输入服务器被研究人员广泛使用，使用这些服务器持有的高保真基因组的其他访问控制参考面板来输入他们的数据。我们报告的证据反驳了一种普遍的假设，即仅通过imputation服务器间接提供对专家组的访问对专家组中的个人构成可以忽略不计的隐私风险。为此，我们提出了自适应构建人工输入样本并解释其输入结果的算法策略，从而准确地重建参考面板单倍型。我们在三个真实基因组的参考面板上说明了这种可能性，用于一系列输入工具和输出设置。此外，我们证明了来自同一个体的重建单倍型可以通过他们的遗传亲属使用我们的贝叶斯连接算法连接起来，这允许个体二倍体基因组的很大一部分被重新组装。我们还提供了当对手持有来自同一种群的不同数量的基因组时，可以连接的面板比例的种群遗传估计。我们的研究结果表明，代入服务器参考面板中的基因组可能容易被重建，这意味着可能需要考虑额外的保护措施。根据我们的研究结果，我们提出了可能的缓解措施。我们的工作说明了对抗算法在发现新的隐私风险方面的价值，有助于向基因组学社区提供安全数据共享实践的信息。在线版本包含补充材料，下载地址：10.1186/s13059-023-03105-6。
Genotype imputation is an essential step in genetic studies to improve data quality and statistical power. Public imputation servers are widely used by researchers to impute their data using otherwise access-controlled reference panels of high-fidelity genomes held by these servers. We report evidence against the prevailing assumption that providing access to panels only indirectly via imputation servers poses a negligible privacy risk to individuals in the panels. To this end, we present algorithmic strategies for adaptively constructing artificial input samples and interpreting their imputation results that lead to the accurate reconstruction of reference panel haplotypes. We illustrate this possibility on three reference panels of real genomes for a range of imputation tools and output settings. Moreover, we demonstrate that reconstructed haplotypes from the same individual could be linked via their genetic relatives using our Bayesian linking algorithm, which allows a substantial portion of the individual’s diploid genome to be reassembled. We also provide population genetic estimates of the proportion of a panel that could be linked when an adversary holds a varying number of genomes from the same population. Our results show that genomes in imputation server reference panels can be vulnerable to reconstruction, implying that additional safeguards may need to be considered. We suggest possible mitigation measures based on our findings. Our work illustrates the value of adversarial algorithms in uncovering new privacy risks to help inform the genomics community towards secure data sharing practices. The online version contains supplementary material available at 10.1186/s13059-023-03105-6.
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DOI：
10.1056/nejmsr1809937
发表时间：
2019-08-15
期刊：
The New England journal of medicine
影响因子：
--
作者：
All of Us Research Program Investigators;Denny JC;Rutter JL;Goldstein DB;Philippakis A;Smoller JW;Jenkins G;Dishman E
通讯作者：
Dishman E
影响因子：
30.8
作者：
Das, Sayantan;Forer, Lukas;Schoenherr, Sebastian;Sidore, Carlo;Locke, Adam E.;Kwong, Alan;Vrieze, Scott I.;Chew, Emily Y.;Levy, Shawn;McGue, Matt;Schlessinger, David;Stambolian, Dwight;Loh, Po-Ru;Iacono, William G.;Swaroop, Anand;Scott, Laura J.;Cucca, Francesco;Kronenberg, Florian;Boehnke, Michael;Abecasis, Goncalo R.;Fuchsberger, Christian
通讯作者：
Fuchsberger, Christian
影响因子：
30.8
作者：
Loh, Po-Ru;Danecek, Petr;Palamara, Pier Francesco;Fuchsberger, Christian;Reshef, Yakir A.;Finucane, Hilary K.;Schoenherr, Sebastian;Forer, Lukas;McCarthy, Shane;Abecasis, Goncalo R.;Durbin, Richard;Price, Alkes L.
通讯作者：
Price, Alkes L.
影响因子：
4.5
作者：
Rubinacci S;Delaneau O;Marchini J
通讯作者：
Marchini J
影响因子：
56.9
作者：
Gymrek, Melissa;McGuire, Amy L.;Erlich, Yaniv
通讯作者：
Erlich, Yaniv