Statistical confidence for likelihood-based paternity inference in natural populations
Statistical confidence for likelihood-based paternity inference in natural populations
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DOI：
10.1046/j.1365-294x.1998.00374.x
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发表时间：
1998-05-01
影响因子：
4.9
通讯作者：
Pemberton, JM
中科院分区：
文献类型：
--
作者：
Marshall, TC;Slate, J;Pemberton, JM
在自然群体的研究中，利用高度多态共显性标记进行亲子关系推断越来越普遍。然而，多个男性往往被发现与每个测试的后代基因兼容，即使排除无关的男性的概率很高。虽然存在各种方法来评估每个非排除男性的亲子关系的可能性，解释这些可能性迄今为止是困难的，没有一种方法考虑到不完整的采样和容易出错的遗传数据的典型的大规模研究的自然系统。我们推导出的似然比亲子推理与共显性标记考虑到分型错误，并定义了一个统计Delta解决亲子关系。使用等位基因频率的研究人口的问题，模拟程序产生的标准德尔塔，允许分配亲子关系的最有可能的男性与一个已知的统计置信水平。模拟考虑了候选男性的数量，被抽样的男性比例以及遗传数据中的差距和错误。我们探讨了潜在的混淆效应的亲属，并表明，该方法是强大的，他们的存在下常见的条件。该方法证明了使用的遗传数据，从深入研究的领导鹿（马鹿）人口的朗姆酒，苏格兰的岛屿。本研究中描述的基于Windows的计算机程序CERVUS dagger可从作者处获得。CERVUS可用于计算等位基因频率，运行模拟并使用来自所有类型的共显性标记的数据进行亲子关系分析。
Paternity inference using highly polymorphic codominant markers is becoming common in the study of natural populations. However, multiple males are often found to be genetically compatible with each offspring tested, even when the probability of excluding an unrelated male is high. While various methods exist for evaluating the likelihood of paternity of each nonexcluded male, interpreting these likelihoods has hitherto been difficult, and no method takes account of the incomplete sampling and error-prone genetic data typical of large-scale studies of natural systems. We derive likelihood ratios for paternity inference with codominant markers taking account of typing error, and define a statistic Delta for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for Delta that permit assignment of paternity to the most likely male with a known level of statistical confidence. The simulation takes account of the number of candidate males, the proportion of males that are sampled and gaps and errors in genetic data. We explore the potentially confounding effect of relatives and show that the method is robust to their presence under commonly encountered conditions. The method is demonstrated using genetic data from the intensively studied led deer (Cervus elaphus) population on the island of Rum, Scotland. The Windows-based computer program, CERVUS dagger, described in this study is available from the authors. CERVUS can be used to calculate allele frequencies, run simulations and perform parentage analysis using data from all types of codominant markers.