美国马萨诸塞州总医院Mark J. Daly研究组建立了拥有39,472个外显子组对照样本的公共平台，使关联研究无需基因型共享。相关论文于2024年1月10日发表在《自然—遗传学》杂志上。

利用奇异值分解和子抽样算法的特性，他们开发了一种方法，允许在符合个人数据保护的外部样本池中选择最匹配的对照，并消除了基因型共享的需要。他们在http://dnascore.net上提供39,472个外显子组测序对照库的访问权限，以便对缺乏对照受试者的病例队列进行关联研究。

使用这种方法，控制集可以从这个在线库中选择，具有预先指定的匹配精度，确保对罕见和常见变异进行良好校准的关联分析。

据了解，获取与病例样本匹配的足够有力的对照样本队列可能很耗时，在某些情况下甚至是不可能的。因此，利用已经从其他地方收集的对照样本的遗传数据的能力，可以大大提高遗传关联研究的能力。由于大多数人类基因数据都受到严格的共享规定的约束，因此共享对照样本可能会带来重大挑战。

附：英文原文

Title: Public platform with 39,472 exome control samples enables association studies without genotype sharing

Author: Artomov, Mykyta, Loboda, Alexander A., Artyomov, Maxim N., Daly, Mark J.

Issue&Volume: 2024-01-10

Abstract: Acquiring a sufficiently powered cohort of control samples matched to a case sample can be time-consuming or, in some cases, impossible. Accordingly, an ability to leverage genetic data from control samples that were already collected elsewhere could dramatically improve power in genetic association studies. Sharing of control samples can pose significant challenges, since most human genetic data are subject to strict sharing regulations. Here, using the properties of singular value decomposition and subsampling algorithm, we developed a method allowing selection of the best-matching controls in an external pool of samples compliant with personal data protection and eliminating the need for genotype sharing. We provide access to a library of 39,472 exome sequencing controls at http://dnascore.net enabling association studies for case cohorts lacking control subjects. Using this approach, control sets can be selected from this online library with a prespecified matching accuracy, ensuring well-calibrated association analysis for both rare and common variants.

DOI: 10.1038/s41588-023-01637-y

Source: https://www.nature.com/articles/s41588-023-01637-y