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A Test for Linkage and Association in General Pedigrees: The Pedigree Disequilibrium Test

机译:普通谱系的联系和关联测试:谱系不平衡测试

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摘要

Family-based tests of linkage disequilibrium typically are based on nuclear-family data including affected individuals and their parents or their unaffected siblings. A limitation of such tests is that they generally are not valid tests of association when data from related nuclear families from larger pedigrees are used. Standard methods require selection of a single nuclear family from any extended pedigrees when testing for linkage disequilibrium. Often data are available for larger pedigrees, and it would be desirable to have a valid test of linkage disequilibrium that can use all potentially informative data. In this study, we present the pedigree disequilibrium test (PDT) for analysis of linkage disequilibrium in general pedigrees. The PDT can use data from related nuclear families from extended pedigrees and is valid even when there is population substructure. Using computer simulations, we demonstrated validity of the test when the asymptotic distribution is used to assess the significance, and examined statistical power. Power simulations demonstrate that, when extended pedigree data are available, substantial gains in power can be attained by use of the PDT rather than existing methods that use only a subset of the data. Furthermore, the PDT remains more powerful even when there is misclassification of unaffected individuals. Our simulations suggest that there may be advantages to using the PDT even if the data consist of independent families without extended family information. Thus, the PDT provides a general test of linkage disequilibrium that can be widely applied to different data structures
机译:基于家庭的连锁不平衡测试通常基于核家庭数据,包括受影响的个人及其父母或未受影响的兄弟姐妹。这种测试的局限性在于,当使用来自较大血统的相关核科的数据时,它们通常不是有效的关联测试。测试链接不平衡时,标准方法要求从任何扩展的谱系中选择一个核心家族。通常情况下,较大的家系可获得数据,因此,希望有一种有效的连锁不平衡测试方法,可以使用所有可能提供信息的数据。在这项研究中,我们提出了谱系不平衡测试(PDT),用于分析一般谱系中的连锁不平衡。 PDT可以使用来自扩展血统的相关核科的数据,即使存在人口子结构,PDT仍然有效。使用计算机模拟,当渐近分布用于评估显着性并检验统计功效时,我们证明了测试的有效性。功率模拟表明,当获得扩展的谱系数据时,可以通过使用PDT而不是仅使用数据子集的现有方法来获得可观的功率提升。此外,即使对未受影响的个人进行了错误分类,PDT仍然具有更强大的功能。我们的模拟表明,即使数据由独立的家族组成而又没有扩展的家族信息,使用PDT还是有优势的。因此,PDT提供了连锁不平衡的一般测试,可以广泛应用于不同的数据结构

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