Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Barcelona, Spain.
Department of Biostatistics, University of Washington, Seattle, WA, USA.
Mol Ecol Resour. 2021 Jul;21(5):1547-1557. doi: 10.1111/1755-0998.13373. Epub 2021 Mar 23.
Statistical methodology for testing the Hardy-Weinberg equilibrium at X chromosomal variants has recently experienced considerable development. Up to a few years ago, testing X chromosomal variants for equilibrium was basically done by applying autosomal test procedures to females only. At present, male alleles can be taken into account in asymptotic and exact test procedures for both the bi- and multiallelic case. However, current X chromosomal exact procedures for multiple alleles rely on a classical full enumeration algorithm and are computationally expensive, and in practice not feasible for more than three alleles. In this article, we extend the autosomal network algorithm for exact Hardy-Weinberg testing with multiple alleles to the X chromosome, achieving considerable reduction in computation times for multiallelic variants with up to five alleles. The performance of the X chromosomal network algorithm is assessed in a simulation study. Beyond four alleles, a permutation test is, in general, the more feasible approach. A detailed description of the algorithm is given, and examples of X chromosomal indels and microsatellites are discussed.
近年来，用于检验 X 染色体变异 Hardy-Weinberg 平衡的统计方法有了相当大的发展。直到几年前，检验 X 染色体变异是否处于平衡状态基本上是通过仅对女性应用常染色体检验程序来完成的。目前，对于双等位基因和多等位基因情况，渐近和精确检验程序都可以考虑男性等位基因。然而，目前用于多个等位基因的 X 染色体精确程序依赖于经典的完全枚举算法，计算成本很高，在实践中对于超过三个等位基因不可行。在本文中，我们将带有多个等位基因的常染色体网络算法扩展到 X 染色体，对于多达五个等位基因的多等位基因变体，大大减少了计算时间。在模拟研究中评估了 X 染色体网络算法的性能。一般来说，超过四个等位基因时，置换检验是更可行的方法。本文详细描述了该算法，并讨论了 X 染色体插入缺失和微卫星的例子。
