{"title":"Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits","authors":"J. Dylan Weissenkampen, Yu Jiang, Scott Eckert, Bibo Jiang, Bingshan Li, Dajiang J. Liu","doi":"10.1002/cphg.83","DOIUrl":null,"url":null,"abstract":"<p>With the advent of Next Generation Sequencing (NGS) technologies, whole genome and whole exome DNA sequencing has become affordable for routine genetic studies. Coupled with improved genotyping arrays and genotype imputation methodologies, it is increasingly feasible to obtain rare genetic variant information in large datasets. Such datasets allow researchers to gain a more complete understanding of the genetic architecture of complex traits caused by rare variants. State-of-the-art statistical methods for the statistical genetics analysis of sequence-based association, including efficient algorithms for association analysis in biobank-scale datasets, gene-association tests, meta-analysis, fine mapping methods that integrate functional genomic dataset, and phenome-wide association studies (PheWAS), are reviewed here. These methods are expected to be highly useful for next generation statistical genetics analysis in the era of precision medicine. © 2019 by John Wiley & Sons, Inc.</p>","PeriodicalId":40007,"journal":{"name":"Current Protocols in Human Genetics","volume":"101 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cphg.83","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Protocols in Human Genetics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cphg.83","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
With the advent of Next Generation Sequencing (NGS) technologies, whole genome and whole exome DNA sequencing has become affordable for routine genetic studies. Coupled with improved genotyping arrays and genotype imputation methodologies, it is increasingly feasible to obtain rare genetic variant information in large datasets. Such datasets allow researchers to gain a more complete understanding of the genetic architecture of complex traits caused by rare variants. State-of-the-art statistical methods for the statistical genetics analysis of sequence-based association, including efficient algorithms for association analysis in biobank-scale datasets, gene-association tests, meta-analysis, fine mapping methods that integrate functional genomic dataset, and phenome-wide association studies (PheWAS), are reviewed here. These methods are expected to be highly useful for next generation statistical genetics analysis in the era of precision medicine. © 2019 by John Wiley & Sons, Inc.
复杂性状相关罕见变异的分析与解释方法
随着下一代测序(NGS)技术的出现,全基因组和全外显子组DNA测序已经成为常规遗传研究的负担得起的方法。随着基因分型阵列和基因型插补方法的改进,在大型数据集中获取罕见遗传变异信息越来越可行。这样的数据集使研究人员能够更全面地了解由罕见变异引起的复杂性状的遗传结构。本文综述了基于序列关联的统计遗传学分析的最新统计方法,包括生物库规模数据集关联分析的高效算法、基因关联测试、元分析、集成功能基因组数据集的精细定位方法和全表型关联研究(PheWAS)。这些方法有望在精准医学时代的下一代统计遗传学分析中发挥重要作用。©2019 by John Wiley &儿子,Inc。
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