Data from: Graphics for relatedness research

Studies of relatedness have been crucial in molecular ecology over the last decades. Good evidence of this is the fact that studies of population structure, evolution of social behaviours, genetic diversity and quantitative genetics all involve relatedness research. The main aim of this article is to review the most common graphical methods used in allele sharing studies for detecting and identifying family relationships. Both IBS and IBD based allele sharing studies are considered. Furthermore, we propose two additional graphical methods from the field of compositional data analysis: the ternary diagram and scatterplots of isometric log-ratios of IBS and IBD probabilities. We illustrate all graphical tools with genetic data from the HGDP-CEPH diversity panel, using mainly 377 microsatellites genotyped for 25 individuals from the Maya population of this panel. We enhance all graphics with convex hulls obtained by simulation and use these to confirm the documented relationships. The proposed compositional graphics are shown to be useful in relatedness research, as they also single out the most prominent related pairs. The ternary diagram is advocated for its ability to display all three allele sharing probabilities simultaneously. The log-ratio plots are advocated as an attempt to overcome the problems with the Euclidean distance interpretation in the classical graphics.

近数十年来，亲缘关系研究在分子生态学领域始终发挥着关键支撑作用。种群结构、社会行为演化、遗传多样性及数量遗传学等方向的研究均涉及亲缘关系分析，这一事实足以佐证上述论断。本文的核心目标为系统梳理用于等位基因共享研究的主流可视化方法，以检测并鉴定家族亲缘关系，其中涵盖基于同一性状态（IBS, Identity By State）与同源同一性（IBD, Identity By Descent）的等位基因共享研究。此外，本文还从成分数据分析领域提出两种全新的可视化方法：三元图（ternary diagram），以及基于IBS与IBD概率的等距对数比散点图。本文采用HGDP-CEPH多样性面板的遗传数据对所有可视化工具进行演示，主要使用该面板中玛雅人群25个个体的377个微卫星（microsatellite）基因型数据。本文通过模拟生成凸包（convex hull）为所有可视化图形添加辅助标注，并借助凸包验证已报道的亲缘关系。实验结果表明，本文提出的成分数据分析可视化方法在亲缘关系研究中具备良好应用价值，可精准识别最显著的亲缘个体对。三元图因可同时展示三种等位基因共享概率，被推荐为首选可视化方案。而对数比散点图则旨在解决经典可视化方法中欧氏距离（Euclidean distance）解释存在的局限。