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An empirical exploration of data quality in DNA-based population inventories

机译:基于DNA的人口清单中数据质量的实证探索

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I present data from 21 population inventory studies - 20 of them on bears - that relied on the noninvasive collection of hair, and review the methods that were used to prevent genetic errors in these studies. These methods were designed to simultaneously minimize errors (which can bias estimates of abundance) and per-sample analysis effort (which can reduce the precision of estimates by limiting sample size). A variety of approaches were used to probe the reliability of the empirical data, producing a mean, per-study estimate of no more than one undetected error in either direction (too few or too many individuals identified in the laboratory). For the type of samples considered here (plucked hair samples), the gain or loss of individuals in the laboratory can be reduced to a level that is inconsequential relative to the more universal sources of bias and imprecision that can affect mark-recapture studies, assuming that marker systems are selected according to stated guidelines, marginal samples are excluded at an early stage, similar pairs of genotypes are scrutinized, and laboratory work is performed with skill and care. [References: 28]
机译:我提出了21项人口调查研究的数据(其中20项是熊),这些数据依赖于头发的非侵入性收集,并回顾了这些研究中用于防止遗传错误的方法。设计这些方法的目的是要同时最小化误差(这可能会使丰度估计值产生偏差)和每个样本的分析工作(可能会通过限制样本大小而降低估计的精度)。多种方法用于探究经验数据的可靠性,从而得出每个研究的平均研究估计值,即在任一方向上均未发现一个错误(在实验室中识别出的个人太少或太多)。对于此处考虑的样本类型(拔毛样本),可以将实验室中个体的得失减少到相对于可能影响标记回收研究的更普遍的偏见和不精确来源无关紧要的水平,假设根据既定指南选择标记系统,在早期排除边缘样本,仔细检查相似的基因型对,并在技巧和谨慎下进行实验室工作。 [参考:28]

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