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

机译:准确公正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率的影响

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摘要

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: Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-017-1172-8) contains supplementary material, which is available to authorized users.
机译:在最近的一项研究中,Petrovski和Goldstein报告说,与非洲人,拉丁裔,南亚人,东亚人和其他未分配的非欧洲人相比,(非芬兰人)欧洲人在线孟德尔遗传(OMIM)疾病基因中的非同义单身显着减少。我们使用Exome Aggregation Consortium(ExAC)数据的模拟来显示样本大小和比率相互影响,以影响队列中确定的这些单例的数量。这些相互作用在祖先之间是不同的,并且可以导致在欧洲人和非欧洲人中相同数量的已确定单身人士而没有相同数量的样本。我们的结论是,有必要考虑人口统计学对基因组架构和稀有变异分析的祖先特定影响,以解决医学基因组分析中的不平等问题。原始文章的作者应邀提交回应,但拒绝了这样做。请参阅相关的公开信:电子补充材料本文的在线版本(doi:10.1186 / s13059-017-1172-8)包含补充材料,授权用户可以使用。

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