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Collapsing SNP Genotypes in Case-Control Genome-Wide Association Studies Increases the Type I Error Rate and Power

机译:在病例对照基因组-全基因组关联研究中,折叠的SNP基因型增加了I型错误率和功效

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摘要

Genome-wide association studies are now widely used tools to identify genes and/or regions which may contribute to the development of various diseases. With case-control data a 2x3 contingency table can be constructed for each SNP to perform genotype-based tests of association. An increasingly common technique to increase the power to detect an association is to collapse each 2x3 table into a table assuming either a dominant or recessive mode of inheritance (2x2 table). We consider three different methods of determining which genetic model to choose and show that each of these methods of collapsing genotypes increases the type I error rate (i.e., the rate of false positives). However, one of these methods does lead to an increase in power compared with the usual genotype- and allele-based tests for most genetic models.
机译:全基因组关联研究现已广泛用于鉴定可能有助于多种疾病发展的基因和/或区域的工具。利用案例控制数据,可以为每个SNP构造一个2x3列联表,以执行基于基因型的关联测试。一种越来越常见的提高关联检测能力的技术是将每个2x3表折叠为一个表,假定该表是显性或隐性继承模式(2x2表)。我们考虑了确定选择哪种遗传模型的三种不同方法,并表明这些折叠基因型的方法均会增加I型错误率(即假阳性率)。但是,与大多数遗传模型的常规基于基因型和等位基因的检测相比,这些方法中的一种确实导致功效的提高。

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