An evolutionary framework for association testing in resequencing studies.
An evolutionary framework for association testing in resequencing studies.
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DOI：
10.1371/journal.pgen.1001202
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发表时间：
2010-11-11
期刊：
影响因子：
4.5
通讯作者：
Nicolae DL
中科院分区：
文献类型：
--
作者：
King CR;Rathouz PJ;Nicolae DL
测序技术变得足够便宜，可以应用于大量的研究参与者，并有望通过揭示罕见的和以前未知的遗传变异来提供对人类表型的新见解。我们开发了一个新的框架序列数据的分析，结合了所有的主要功能，以前提出的方法，包括那些专注于等位基因计数和等位基因负担，但更普遍和更强大的。我们利用群体遗传学理论来提供关于效应大小的先验信息，并为来自罕见变异的信息创建一个汇集策略。我们的方法，EMMPAT（进化混合模型池关联测试），每个基因产生一个单一的测试（大大减少了多个测试的关注），便于图形总结，并通过允许计算归因方差，提高了结果的解释。模拟结果表明，相对于以前使用的方法，我们的方法增加了力量来检测影响表型的基因时，自然选择保持了大的效应大小罕见的等位基因。我们在一项基于人群的血清甘油三酯与ANGPTL4变异之间相关性的重新测序研究中展示了我们的方法。将遗传变异与疾病和其他人类特征相关联的研究主要研究了常见的突变，部分原因是技术限制。然而，最近的进展已经导致获得基因组序列数据的成本急剧下降，这为检测罕见的遗传变异提供了机会。为早期技术设计的现有分析方法对于发现与罕见突变的联系并不是最佳的。我们利用1）对进化机制的先进理论理解和2）关于人类基因组进化力量的全基因组证据，提出了一个理解罕见遗传变异和现代特征之间观察到的相关性的框架。该模型导致一个强大的测试遗传关联和改进的解释结果。我们证明了新的方法对先前确认的结果在基因相关的高血胆固醇水平。
Sequencing technologies are becoming cheap enough to apply to large numbers of study participants and promise to provide new insights into human phenotypes by bringing to light rare and previously unknown genetic variants. We develop a new framework for the analysis of sequence data that incorporates all of the major features of previously proposed approaches, including those focused on allele counts and allele burden, but is both more general and more powerful. We harness population genetic theory to provide prior information on effect sizes and to create a pooling strategy for information from rare variants. Our method, EMMPAT (Evolutionary Mixed Model for Pooled Association Testing), generates a single test per gene (substantially reducing multiple testing concerns), facilitates graphical summaries, and improves the interpretation of results by allowing calculation of attributable variance. Simulations show that, relative to previously used approaches, our method increases the power to detect genes that affect phenotype when natural selection has kept alleles with large effect sizes rare. We demonstrate our approach on a population-based re-sequencing study of association between serum triglycerides and variation in ANGPTL4. Studies correlating genetic variation to disease and other human traits have examined mostly common mutations, partly because of technological restrictions. However, recent advances have resulted in dramatically declining costs of obtaining genomic sequence data, which provides the opportunity to detect rare genetic variation. Existing methods of analysis designed for an earlier era of technology are not optimal for discovering links to rare mutations. We take advantage of 1) the advanced theoretical understanding of evolutionary mechanics and 2) genome-wide evidence about evolutionary forces on the human genome to suggest a framework for understanding observed correlations between rare genetic variation and modern traits. The model leads to a powerful test for genetic association and to an improved interpretation of results. We demonstrate the new method on previously confirmed results in a gene related to high blood cholesterol levels.
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影响因子：
4.5
作者：
Gutenkunst RN;Hernandez RD;Williamson SH;Bustamante CD
通讯作者：
Bustamante CD
DOI：
10.1073/pnas.0906182107
发表时间：
2010-01-26
影响因子：
11.1
作者：
Eyre-Walker, Adam
通讯作者：
Eyre-Walker, Adam
影响因子：
5.8
作者：
Hernandez, Ryan D.
通讯作者：
Hernandez, Ryan D.
DOI：
10.1073/pnas.0812824106
发表时间：
2009-03-10
影响因子：
11.1
作者：
Kryukov, Gregory V.;Shpunt, Alexander;Sunyaev, Shamil R.
通讯作者：
Sunyaev, Shamil R.
影响因子：
13.5
作者：
Browning, JD;Szczepaniak, LS;Hobbs, HH
通讯作者：
Hobbs, HH