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准确且公平的医学基因组分析需要了解人口统计学及其对样本量和比例的影响。

Accurate and equitable medical genomic analysis requires an understanding of demography and its influence on sample size and ratio.

作者信息

Kessler Michael D, O'Connor Timothy D

机构信息

Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.

Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.

出版信息

Genome Biol. 2017 Feb 27;18(1):42. doi: 10.1186/s13059-017-1172-8.

Abstract

In a recent study, Petrovski and Goldstein reported that (non-Finnish) Europeans have significantly fewer nonsynonymous singletons in Online Mendelian Inheritance in Man (OMIM) disease genes compared with Africans, Latinos, South Asians, East Asians, and other unassigned non-Europeans. We use simulations of Exome Aggregation Consortium (ExAC) data to show that sample size and ratio interact to influence the number of these singletons identified in a cohort. These interactions are different across ancestries and can lead to the same number of identified singletons in both Europeans and non-Europeans without an equal number of samples. We conclude that there is a need to account for the ancestry-specific influence of demography on genomic architecture and rare variant analysis in order to address inequalities in medical genomic analysis.The authors of the original article were invited to submit a response, but declined to do so. Please see related Open Letter: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1016-y.

摘要

在最近的一项研究中,彼得罗夫斯基和戈尔茨坦报告称,与非洲人、拉丁裔、南亚人、东亚人及其他未分类的非欧洲人相比,(非芬兰)欧洲人在线《人类孟德尔遗传》(OMIM)疾病基因中的非同义单例显著更少。我们通过对外显子聚合联盟(ExAC)数据进行模拟,以表明样本量和比例相互作用会影响在一个队列中识别出的这些单例数量。这些相互作用在不同血统中有所不同,并且可能导致在欧洲人和非欧洲人中识别出相同数量的单例,而样本数量并不相等。我们得出结论,有必要考虑人口统计学对基因组结构和罕见变异分析的特定血统影响,以解决医学基因组分析中的不平等问题。原文章的作者受邀提交回应,但拒绝这样做。请参阅相关公开信:http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1016-y

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/181b/5330117/c877aeb9bd92/13059_2017_1172_Fig1_HTML.jpg

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