Effect of linkage disequilibrium on the identification of functional variants.
Effect of linkage disequilibrium on the identification of functional variants.
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DOI：
10.1002/gepi.20660
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发表时间：
2011
影响因子：
2.1
通讯作者：
Paterson, Andrew D.
中科院分区：
文献类型：
--
作者：
Thomas, Alun;Abel, Haley J.;Di, Yanming;Faye, Laura L.;Jin, Jing;Liu, Jin;Wu, Zheyan;Paterson, Andrew D.
关键词：
我们总结了第17届遗传分析研讨会第9组的贡献。该小组讨论了连锁不平衡和其他较长范围的等位基因关联形式在评估基因对表型的影响时的问题。长期协会提出的问题，无论是由于选择、分层、可能的技术错误或偶然性，都不那么令人期待，但事实证明是重要的。大多数贡献者专注于各种类型的回归方法，以说明有问题的问题或开发处理高密度基因分析的适应方法。研究设计也被考虑，图形建模也是如此。尽管没有统一成功的方法出现，但大多数方法都成功地减少了假阳性结果，要么是考虑了基因内的基因座集群，要么是应用了平滑度量标准，要求相邻基因座的结果相似。观察到了两个意想不到的结果，它们质疑我们关于建立连锁不平衡模型所需条件的假设。首先，被很大遗传距离隔开的基因座之间的相关性可能会极大地夸大单基因座检验统计量，无论是选择、分层、可能的技术错误还是偶然的结果，这些相关性似乎都过多了。第二个意想不到的结果是，将主成分分析应用于全基因组基因数据，不仅可以明显控制群体结构，还可以控制连锁不平衡。
We summarize the contributions of Group 9 of Genetic Analysis Workshop 17. This group addressed the problems of linkage disequilibrium and other longer range forms of allelic association when evaluating the effects of genotypes on phenotypes. Issues raised by long-range associations, whether a result of selection, stratification, possible technical errors, or chance, were less expected but proved to be important. Most contributors focused on regression methods of various types to illustrate problematic issues or to develop adaptations for dealing with high-density genotype assays. Study design was also considered, as was graphical modeling. Although no method emerged as uniformly successful, most succeeded in reducing false-positive results either by considering clusters of loci within genes or by applying smoothing metrics that required results from adjacent loci to be similar. Two unexpected results that questioned our assumptions of what is required to model linkage disequilibrium were observed. The first was that correlations between loci separated by large genetic distances can greatly inflate single-locus test statistics, and, whether the result of selection, stratification, possible technical errors, or chance, these correlations seem overabundant. The second unexpected result was that applying principal components analysis to genome-wide genotype data can apparently control not only for population structure but also for linkage disequilibrium.
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影响因子：
--
作者：
Abel HJ;Thomas A
通讯作者：
Thomas A
影响因子：
4.5
作者：
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通讯作者：
Zhang, Cun-Hui
影响因子：
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作者：
He, Shiquan;Wu, Zheyang
通讯作者：
Wu, Zheyang
影响因子：
2.1
作者：
Thomas, A
通讯作者：
Thomas, A
影响因子：
--
作者：
Liu J;Wang K;Ma S;Huang J
通讯作者：
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