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在模拟环境中量化二次校准与远距离一次校准的误差。

Quantifying the Error of Secondary vs. Distant Primary Calibrations in a Simulated Environment.

作者信息

Powell Christopher Lowell Edward, Waskin Sydney, Battistuzzi Fabia Ursula

机构信息

Department of Biological Sciences, Oakland University, Rochester, MI, United States.

Center for Data Science and Big Data Analytics, Oakland University, Rochester, MI, United States.

出版信息

Front Genet. 2020 Mar 20;11:252. doi: 10.3389/fgene.2020.00252. eCollection 2020.

Abstract

Using calibrations to obtain absolute divergence times is standard practice in molecular clock studies. While the use of primary (e.g., fossil) calibrations is preferred, this approach can be limiting because of their rarity in fast-growing datasets. Thus, alternatives need to be explored, such as the use of secondary (molecularly-derived) calibrations that can anchor a timetree in a larger number of nodes. However, the use of secondary calibrations has been discouraged in the past because of concerns in the error rates of the node estimates they produce with an apparent high precision. Here, we quantify the amount of errors in estimates produced by the use of secondary calibrations relative to true times and primary calibrations placed on distant nodes. We find that, overall, the inaccuracies in estimates based on secondary calibrations are predictable and mirror errors associated with primary calibrations and their confidence intervals. Additionally, we find comparable error rates in estimated times from secondary calibrations and distant primary calibrations, although the precision of estimates derived from distant primary calibrations is roughly twice as good as that of estimates derived from secondary calibrations. This suggests that increasing dataset size to include primary calibrations may produce divergence times that are about as accurate as those from secondary calibrations, albeit with a higher precision. Overall, our results suggest that secondary calibrations may be useful to explore the parameter space of plausible evolutionary scenarios when compared to time estimates obtained with distant primary calibrations.

摘要

在分子钟研究中,使用校准来获得绝对分歧时间是标准做法。虽然首选使用主要(如化石)校准,但由于其在快速增长的数据集中较为罕见,这种方法可能存在局限性。因此,需要探索替代方法,例如使用次要(分子衍生)校准,它可以在更多节点上锚定时间树。然而,过去由于担心次要校准产生的节点估计误差率明显较高,人们不鼓励使用次要校准。在此,我们量化了使用次要校准相对于真实时间和置于较远节点的主要校准所产生的估计误差量。我们发现,总体而言,基于次要校准的估计误差是可预测的,并且反映了与主要校准及其置信区间相关的误差。此外,我们发现次要校准和远距离主要校准的估计时间误差率相当,尽管远距离主要校准的估计精度大约是次要校准的两倍。这表明增加数据集大小以纳入主要校准可能会产生与次要校准一样准确的分歧时间,尽管精度更高。总体而言,我们的结果表明,与使用远距离主要校准获得的时间估计相比,次要校准可能有助于探索合理进化情景的参数空间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f3/7099002/e1d9094b9af0/fgene-11-00252-g001.jpg

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