Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, The Netherlands.
Methods Mol Biol. 2023;2545:261-277. doi: 10.1007/978-1-0716-2561-3_14.
Analyzing autopolyploid genetic data still presents numerous challenges due to, e.g., missing dosage information of genotypes and the presence of multiple ploidy levels within species or populations, but also because the choice of software is limited when compared to what is available for diploid data. However, over the last years, the number of software programs that can deal with polyploid data is slowly increasing. The software GENODIVE is one of the most widely used programs for the analysis of polyploid genetic data, presenting a wide array of different methods. In this chapter, I outline several frequently used types of population genetic analyses and explain how these apply to polyploid data, including possible pitfalls and biases. I then explain how GENODIVE approaches these analyses and whether and how it can overcome possible biases. Specifically, I focus on analyses of genetic diversity, Hardy-Weinberg equilibrium, quantifying population differentiation, clustering, and calculation of genetic distances. GENODIVE can be downloaded freely from http://www.patrickmeirmans.com/software .
由于基因型的剂量信息缺失以及物种或种群内存在多个倍性水平等原因，分析自倍性遗传数据仍然存在诸多挑战，但与二倍体数据相比，可用于分析的软件选择也很有限。然而，在过去几年中，能够处理多倍体数据的软件程序的数量正在缓慢增加。GENODIVE 软件是分析多倍体遗传数据最广泛使用的程序之一，它提供了多种不同的方法。在本章中，我概述了几种常用的群体遗传分析类型，并解释了它们如何应用于多倍体数据，包括可能的陷阱和偏差。然后，我解释了 GENODIVE 如何处理这些分析，以及它是否以及如何克服可能的偏差。具体来说，我重点分析了遗传多样性、哈迪-温伯格平衡、种群分化的量化、聚类和遗传距离的计算。GENODIVE 可以从 http://www.patrickmeirmans.com/software 免费下载。
