Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania.
Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania.
Genome Biol Evol. 2020 Feb 1;12(2):3873-3877. doi: 10.1093/gbe/evaa013.
Long-term balancing selection results in a build-up of alleles at similar frequencies and a deficit of substitutions when compared with an outgroup at a locus. The previously published β(1) statistics detect balancing selection using only polymorphism data. We now propose the β(2) statistic which detects balancing selection using both polymorphism and substitution data. In addition, we derive the variance of all β statistics, allowing for their standardization and thereby reducing the influence of parameters which can confound other selection tests. The standardized β statistics outperform existing summary statistics in simulations, indicating β is a well-powered and widely applicable approach for detecting balancing selection. We apply the β(2) statistic to 1000 Genomes data and report two missense mutations with high β scores in the ACSBG2 gene. An implementation of all β statistics and their standardization are available in the BetaScan2 software package at https://github.com/ksiewert/BetaScan.
当与外群比较时,长期的平衡选择会导致相似频率等位基因的积累,以及替代物的缺乏。以前发表的β(1)统计数据仅使用多态性数据检测平衡选择。我们现在提出β(2)统计数据,该数据使用多态性和替换数据来检测平衡选择。此外,我们推导出所有β统计数据的方差,允许对其进行标准化,从而减少可能混淆其他选择测试的参数的影响。标准化的β统计数据在模拟中优于现有的汇总统计数据,这表明β是一种功能强大且广泛适用的检测平衡选择的方法。我们将β(2)统计数据应用于 1000 基因组数据,并报告了 ACSBG2 基因中两个具有高β分数的错义突变。所有β统计数据及其标准化的实现都可以在 https://github.com/ksiewert/BetaScan 上的 BetaScan2 软件包中获得。