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Detecting dyads of related individuals in large collections of DNA-profiles by controlling the false discovery rate

机译:通过控制错误发现率来检测大量DNA概况中相关个人的二元

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The search for pairs (dyads) of related individuals in large databases of DNA-profiles has become an increasingly important inference tool in ecology. However, the many, partly dependent, pairwise comparisons introduce statistical issues. We show that the false discovery rate (FDR) procedure is well suited to control for the proportion of false positives, i.e. dyads consisting of unrelated individuals, which under normal circumstances would have been labelled as related individuals.We verify the behaviour of the standard FDR procedure by simulation, demonstrating that the FDR procedure works satisfactory in spite of the many dependent pairwise comparisons involved in an exhaustive database screening. A computer program that implements this method is available online. In addition, we propose to implement a second stage in the procedure, in which additional independent genetic markers are used to identify the false positives. We demonstrate the application of the approach in an analysis of a DNA database consisting of 3300 individual minke whales (Balaenoptera acutorostrata) each typed at ten microsatellite loci. Applying the standard procedure with an FDR of 50% led to the identification of 74 putative dyads of 1st- or 2nd-order relatives. However, introducing the second step, which involved additional genotypes at 15 microsatellite loci, revealed that only 21 of the putative dyads can be claimed with high certainty to be true dyads.
机译:在大型的DNA谱数据库中寻找相关个体的对(二元组)已成为生态学中越来越重要的推理工具。但是,许多部分相关的成对比较引入了统计问题。我们表明,错误发现率(FDR)程序非常适合控制错误阳性的比例,即由不相关个体组成的二元组,在正常情况下,它们会被标记为相关个体。我们验证了标准FDR的行为程序通过仿真,表明尽管在详尽的数据库筛选中涉及许多相关的成对比较,但FDR程序仍能令人满意。可以在线获得实现此方法的计算机程序。此外,我们建议在程序中实施第二阶段,其中使用其他独立的遗传标记来识别假阳性。我们证明了该方法在由3300条小须鲸(Balaenoptera acutorostrata)组成的DNA数据库的分析中的应用,每条鲸鱼在十个微卫星基因座处分型。采用FDR为50%的标准程序可以鉴定出74个1级或2级亲戚的二元组。但是,在第二步中引入涉及15个微卫星基因座的其他基因型的步骤表明,只有21个推定的二元组可以被高度确定为真正的二元组。

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