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贝叶斯随机局部时钟,或一统天下的单一速率。

Bayesian random local clocks, or one rate to rule them all.

机构信息

Allan Wilson Centre for Molecular Ecology and Evolution, University of Auckland, Private Bag 92019, Auckland, New Zealand.

出版信息

BMC Biol. 2010 Aug 31;8:114. doi: 10.1186/1741-7007-8-114.

Abstract

BACKGROUND

Relaxed molecular clock models allow divergence time dating and "relaxed phylogenetic" inference, in which a time tree is estimated in the face of unequal rates across lineages. We present a new method for relaxing the assumption of a strict molecular clock using Markov chain Monte Carlo to implement Bayesian modeling averaging over random local molecular clocks. The new method approaches the problem of rate variation among lineages by proposing a series of local molecular clocks, each extending over a subregion of the full phylogeny. Each branch in a phylogeny (subtending a clade) is a possible location for a change of rate from one local clock to a new one. Thus, including both the global molecular clock and the unconstrained model results, there are a total of 2(2n-2) possible rate models available for averaging with 1, 2, ..., 2n - 2 different rate categories.

RESULTS

We propose an efficient method to sample this model space while simultaneously estimating the phylogeny. The new method conveniently allows a direct test of the strict molecular clock, in which one rate rules them all, against a large array of alternative local molecular clock models. We illustrate the method's utility on three example data sets involving mammal, primate and influenza evolution. Finally, we explore methods to visualize the complex posterior distribution that results from inference under such models.

CONCLUSIONS

The examples suggest that large sequence datasets may only require a small number of local molecular clocks to reconcile their branch lengths with a time scale. All of the analyses described here are implemented in the open access software package BEAST 1.5.4 (http://beast-mcmc.googlecode.com/).

摘要

背景

放松分子钟模型允许对分歧时间进行估计,并进行“放松的系统发育”推断,即面对谱系间的不等速率,估计时间树。我们提出了一种新方法,通过马尔可夫链蒙特卡罗(MCMC)来放松严格分子钟的假设,从而实现对随机局部分子钟的贝叶斯模型平均的推断。新方法通过提出一系列局部分子钟来解决谱系间速率变化的问题,每个局部分子钟都涵盖整个系统发育的一个子区域。系统发育中的每个分支(支撑一个分支)都是从一个局部时钟到新时钟的速率变化的可能位置。因此,包括全局分子钟和无约束模型的结果,总共有 2(2n-2)个可能的速率模型可供平均,共有 1、2、...、2n-2 个不同的速率类别。

结果

我们提出了一种高效的方法来对这个模型空间进行抽样,同时估计系统发育。新方法方便地允许对严格分子钟进行直接测试,即将所有速率统一起来的单一速率模型,与大量替代的局部分子钟模型进行对比。我们在三个涉及哺乳动物、灵长类动物和流感进化的示例数据集上展示了该方法的实用性。最后,我们探讨了可视化复杂后验分布的方法,这些方法是在这些模型下进行推断的结果。

结论

这些例子表明,大型序列数据集可能只需要少量的局部分子钟就可以将其分支长度与时间尺度相协调。本文描述的所有分析都在开放访问软件包 BEAST 1.5.4 中实现(http://beast-mcmc.googlecode.com/)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3793/2949620/848595749011/1741-7007-8-114-1.jpg

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