Modified Hudson-Kreitman-Aguade test and two-dimensional evaluation of neutrality tests.
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.
Innan
Hideki
H
Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, Texas 77030, USA. innan_hideki@soken.ac.jp
D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005069:Evaluation Studies as Topic; D005828:Genetics, Population / Q000379:methods*; D016013:Likelihood Functions; D008957:Models, Genetic; D011110:Polymorphism, Genetic