Data from: Relative accuracy of three common methods of parentage analysis in natural populations

Parentage studies and family reconstructions have become increasingly popular for investigating a range of evolutionary, ecological and behavioral processes in natural populations. However, a number of different assignment methods have emerged in common use, and the accuracy of each may differ in relation to the number of loci examined, allelic diversity, incomplete sampling of all candidate parents, and the presence of genotyping errors. Here we examine how these factors affect the accuracy of three popular parentage inference methods (COLONY, FaMoz and an exclusion-Bayes’ theorem approach by Christie et al. (2010a)) to resolve true parent-offspring pairs using simulated data. Our findings demonstrate that accuracy increases with the number and diversity of loci. These were clearly the most important factors in obtaining accurate assignments explaining 75-90% of variance in overall accuracy across 60 simulated scenarios. Furthermore, the proportion of candidate parents sampled had a small but significant impact on the susceptibility of each method to either false positive or false negative assignments. Within the range of values simulated, COLONY outperformed FaMoz, which outperformed the exclusion-Bayes’ theorem method. However, with 20 or more highly polymorphic loci, all methods could be applied with confidence. Our results show that for parentage inference in natural populations, careful consideration of the number and quality of markers will increase the accuracy of assignments and mitigate the effects of incomplete sampling of parental populations.

亲权分析（Parentage studies）与家系重建（family reconstructions）在探究自然种群中各类进化、生态与行为过程的研究中愈发受到重视。然而，目前已涌现出多种常用的亲子鉴定赋值方法，且每种方法的准确性会因所检测的基因座（loci）数量、等位基因多样性、候选亲本抽样不全以及基因分型误差（genotyping errors）等因素而存在差异。本研究借助模拟数据，探究上述因素对三种主流亲权推断方法——COLONY、FaMoz以及Christie等人（2010a）提出的排除法-贝叶斯定理（exclusion-Bayes’ theorem）结合策略——甄别真实亲子对的准确性的影响。研究结果显示，方法准确性随基因座数量与等位基因多样性的提升而升高，这显然是获得准确赋值结果的最关键因素，在60个模拟场景中，该因素可解释整体准确性75%至90%的变异量。此外，候选亲本的抽样比例虽对准确性影响程度较小，但仍会显著影响每种方法出现假阳性（false positive）或假阴性（false negative）赋值结果的概率。在本次模拟的参数范围内，COLONY的表现优于FaMoz，而FaMoz又优于前述的排除法-贝叶斯定理结合方法。但当使用20个及以上高度多态性基因座时，所有方法均可可靠应用。本研究结果表明，针对自然种群的亲权推断研究，审慎考量分子标记的数量与质量，可提升赋值结果的准确性，并缓解亲本种群抽样不全带来的负面影响。