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Mitigating scoring errors in microsatellite data from wild populations

机译:减轻野生种群微卫星数据的评分误差

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摘要

Microsatellite data are widely used to test ecological and evolutionary hypotheses in wild populations. In this paper, we consider three typical sources of scoring errors capable of biasing biological conclusions: stuttering, large-allele dropout and null alleles. We describe methods to detect errors and propose conventions to mitigate scoring errors and report error rates in studies of wild populations. Finally, we discuss potential bias in ecological or evolutionary conclusions based on data sets containing these scoring errors.
机译:微卫星数据被广泛用于测试野生种群中的生态和进化假设。在本文中,我们考虑了能够使生物学结论产生偏差的三种典型评分错误来源:口吃,大等位基因缺失和无效等位基因。我们描述了检测错误的方法,并提出了减轻野生动物研究中评分错误和报告错误率的惯例。最后,我们基于包含这些评分误差的数据集,讨论了生态学或进化论结论中的潜在偏差。

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