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A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches

机译:一种简单的二维非参数重采样统计方法,可评估DNA条形码中物种识别的可信度-一种替代可能性和贝叶斯方法的方法

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摘要

In the recent worldwide campaign for the global biodiversity inventory via DNA barcoding, a simple and easily used measure of confidence for assigning sequences to species in DNA barcoding has not been established so far, although the likelihood ratio test and the Bayesian approach had been proposed to address this issue from a statistical point of view. The TDR (Two Dimensional non-parametric Resampling) measure newly proposed in this study offers users a simple and easy approach to evaluate the confidence of species membership in DNA barcoding projects. We assessed the validity and robustness of the TDR approach using datasets simulated under coalescent models, and an empirical dataset, and found that TDR measure is very robust in assessing species membership of DNA barcoding. In contrast to the likelihood ratio test and Bayesian approach, the TDR method stands out due to simplicity in both concepts and calculations, with little in the way of restrictive population genetic assumptions. To implement this approach we have developed a computer program package (TDR1.0beta) freely available from .
机译:在最近的通过DNA条形码进行的全球生物多样性清单的全球运动中,尽管已经提出了一种简单易用的对DNA条形码中的物种分配序列的置信度的测量方法,尽管已经提出了似然比检验和贝叶斯方法。从统计角度解决此问题。这项研究中新提出的TDR(二维非参数重采样)度量为用户提供了一种简单易行的方法来评估DNA条形码项目中物种成员的置信度。我们使用合并模型下模拟的数据集和经验数据集评估了TDR方法的有效性和鲁棒性,发现TDR度量在评估DNA条形码的物种成员方面非常强大。与似然比检验和贝叶斯方法相比,TDR方法在概念和计算上都非常简单,而在限制性人群遗传假设方面却很少。为实现此方法,我们开发了可从上免费获得的计算机程序包(TDR1.0beta)。

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