Quantifying MCMC exploration of phylogenetic tree space.

Quantifying MCMC exploration of phylogenetic tree space.
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量化系统发育树空间的MCMC探索。

DOI:
10.1093/sysbio/syv006
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发表时间:
2015-05
期刊:
影响因子:
6.5
通讯作者:
Matsen FA 4th
Matsen FA 4th
中科院分区:
生物学1区
文献类型:
--
作者:
Whidden C;Matsen FA 4th

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为了了解系统发育马尔可夫链蒙特卡罗(MCMC)的有效性,重要的是要了解MCMC的经验分布收敛到后验分布的速度。在这篇文章中,我们调查这个问题的系统发育树拓扑结构的度量,特别适合的任务:子树修剪和移植(SPR)度量。该度量直接对应于常见系统发育MCMC实现中在树之间移动所需的MCMC重排的最小数量。我们开发了一种新的基于图的方法来分析树后验,并发现SPR度量比与MCMC移动无关的简单度量更具信息性。在这样做时,我们得出结论,拓扑峰确实发生在贝叶斯系统发育后验从真实的数据集采样与标准MCMC方法,调查的效率,大都市耦合MCMCMC(MCMCMCMC)在穿越峰之间的山谷,并表明条件分支分布(CCD)可能有系统的问题时,有多个峰。
In order to gain an understanding of the effectiveness of phylogenetic Markov chain Monte Carlo (MCMC), it is important to understand how quickly the empirical distribution of the MCMC converges to the posterior distribution. In this article, we investigate this problem on phylogenetic tree topologies with a metric that is especially well suited to the task: the subtree prune-and-regraft (SPR) metric. This metric directly corresponds to the minimum number of MCMC rearrangements required to move between trees in common phylogenetic MCMC implementations. We develop a novel graph-based approach to analyze tree posteriors and find that the SPR metric is much more informative than simpler metrics that are unrelated to MCMC moves. In doing so, we show conclusively that topological peaks do occur in Bayesian phylogenetic posteriors from real data sets as sampled with standard MCMC approaches, investigate the efficiency of Metropolis-coupled MCMC (MCMCMC) in traversing the valleys between peaks, and show that conditional clade distribution (CCD) can have systematic problems when there are multiple peaks.
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