Innan Hideki
Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, Texas 77030, USA.
Genetics. 2006 Jul;173(3):1725-33. doi: 10.1534/genetics.106.056242. Epub 2006 Apr 19.
There are a number of polymorphism-based statistical tests of neutrality, but most of them focus on either the amount or the pattern of polymorphism. In this article, a new test called the two-dimensional (2D) test is developed. This test evaluates a pair of summary statistics in a two-dimensional field. One statistic should summarize the pattern of polymorphism, while the other could be a measure of the level of polymorphism. For the latter summary statistic, the polymorphism-divergence ratio is used following the idea of the Hudson-Kreitman-Aguadé (HKA) test. To incorporate the HKA test in the 2D test, a summary statistic-based version of the HKA test is developed such that the polymorphism-divergence ratio at a particular region of interest is examined if it is consistent with the average of those in other independent regions.
有许多基于多态性的中性统计检验方法，但其中大多数要么关注多态性的数量，要么关注多态性的模式。在本文中，开发了一种名为二维（2D）检验的新检验方法。该检验在二维领域评估一对汇总统计量。一个统计量应总结多态性模式，而另一个可以是多态性水平的度量。对于后一个汇总统计量，遵循哈德森-克赖特曼-阿瓜德（HKA）检验的思想，使用多态性-分化率。为了将HKA检验纳入二维检验，开发了基于汇总统计量的HKA检验版本，以便检查特定感兴趣区域的多态性-分化率是否与其他独立区域的平均值一致。
