Modeling haplotype-haplotype interactions in case-control genetic association studies.
Modeling haplotype-haplotype interactions in case-control genetic association studies.
复制标题
在病例对照遗传关联研究中，建模单倍型 - 型 - 单型相互作用。
DOI：
10.3389/fgene.2012.00002
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发表时间：
2012
影响因子：
3.7
通讯作者：
Wu R
中科院分区：
文献类型：
--
作者：
Zhang L;Liu R;Wang Z;Culver DA;Wu R
单倍型分析已越来越多地用于研究人类疾病的遗传基础，但当前文献中尚未很好地开发表征不同染色体区域单倍型之间遗传相互作用的模型。在本文中，我们描述了一种统计模型，用于通过病例对照遗传关联设计来测试人类疾病的单倍型-单倍型相互作用。该模型是在列联表上制定的，其中针对同一组分子标记键入病例和对照。通过整合完善的定量遗传原理，该模型能够表征来自不同染色体区域的单倍型之间的相互作用所产生的具有生理意义的上位性。该模型允许由于加性 × 加性、加性 × 显性、显性 × 加性和显性 × 显性相互作用将上位性划分为不同的分量。我们推导出 EM 算法来估计和测试每个组件对病例和对照之间遗传变异模式差异的影响，从而检查它们在人类疾病发病机制中的作用。该方法进一步扩展到研究在单倍型水平上表达的基因-环境相互作用。通过模拟研究研究了模型的统计特性，并通过分析人类遗传学项目中结节病的遗传关联来验证其有效性和利用率。
Haplotype analysis has been increasingly used to study the genetic basis of human diseases, but models for characterizing genetic interactions between haplotypes from different chromosomal regions have not been well developed in the current literature. In this article, we describe a statistical model for testing haplotype-haplotype interactions for human diseases with a case-control genetic association design. The model is formulated on a contingency table in which cases and controls are typed for the same set of molecular markers. By integrating well-established quantitative genetic principles, the model is equipped with a capacity to characterize physiologically meaningful epistasis arising from interactions between haplotypes from different chromosomal regions. The model allows the partition of epistasis into different components due to additive × additive, additive × dominance, dominance × additive, and dominance × dominance interactions. We derive the EM algorithm to estimate and test the effects of each of these components on differences in the pattern of genetic variation between cases and controls and, therefore, examine their role in the pathogenesis of human diseases. The method was further extended to investigate gene-environment interactions expressed at the haplotype level. The statistical properties of the models were investigated through simulation studies and its usefulness and utilization validated by analyzing the genetic association of sarcoidosis from a human genetics project.
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影响因子：
2.1
作者：
An, Ping;Mukherjee, Odity;Province, Michael A.
通讯作者：
Province, Michael A.
影响因子：
30.8
作者：
Martin, MP;Gao, XJ;Carrington, M
通讯作者：
Carrington, M
影响因子：
2
作者：
Li, Hongying;Kim, Bong-Rae;Wu, Rongling
通讯作者：
Wu, Rongling
影响因子：
4.4
作者：
Gayán J;González-Pérez A;Bermudo F;Sáez ME;Royo JL;Quintas A;Galan JJ;Morón FJ;Ramirez-Lorca R;Real LM;Ruiz A
通讯作者：
Ruiz A
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y