Design of DNA pooling to allow incorporation of covariates in rare variants analysis.
Design of DNA pooling to allow incorporation of covariates in rare variants analysis.
复制标题
DOI：
10.1371/journal.pone.0114523
复制
发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Li C
中科院分区：
文献类型：
--
作者：
Guan W;Li C
下一代测序技术的快速发展促进了对越来越广泛的罕见变异的遗传关联研究。为了捕捉罕见或不太常见的变异，需要大量的个体。然而，使用全基因组或外显子组测序进行大规模研究的成本仍然很高。 DNA池可以作为一种具有成本效益的方法，但有一个潜在的限制，即个体基因组的身份会丢失，因此个体特征和环境因素无法在关联分析中进行调整，这可能会导致功率损失和遗传效应估计的偏差。对于病例对照研究，我们提出了一种池创建的设计策略和一种允许使用多重插补技术进行协变量调整的分析策略。模拟表明，与昂贵得多的个体基因组测序方法相比，我们的方法可以获得基因型效应的合理估计，而功率仅略有损失。我们的设计和分析策略能够对复杂疾病进行更强大且更具成本效益的测序研究，同时允许纳入协变量调整。
Rapid advances in next-generation sequencing technologies facilitate genetic association studies of an increasingly wide array of rare variants. To capture the rare or less common variants, a large number of individuals will be needed. However, the cost of a large scale study using whole genome or exome sequencing is still high. DNA pooling can serve as a cost-effective approach, but with a potential limitation that the identity of individual genomes would be lost and therefore individual characteristics and environmental factors could not be adjusted in association analysis, which may result in power loss and a biased estimate of genetic effect. For case-control studies, we propose a design strategy for pool creation and an analysis strategy that allows covariate adjustment, using multiple imputation technique. Simulations show that our approach can obtain reasonable estimate for genotypic effect with only slight loss of power compared to the much more expensive approach of sequencing individual genomes. Our design and analysis strategies enable more powerful and cost-effective sequencing studies of complex diseases, while allowing incorporation of covariate adjustment.
登录
查看更多内容
来自1,092个人基因组的遗传变异的综合图。
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
9.8
作者：
Auer, Paul L.;Johnsen, Jill M.;Li, Yun
通讯作者：
Li, Yun
影响因子：
1.9
作者：
Weinberg, CR;Umbach, DM
通讯作者：
Umbach, DM
影响因子：
3.7
作者：
Bansal, Vikas;Tewhey, Ryan;Schork, Nicholas J.
通讯作者：
Schork, Nicholas J.
影响因子：
9.8
作者：
Wu, Michael C.;Kraft, Peter;Lin, Xihong
通讯作者：
Lin, Xihong