AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics
AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics
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DOI：
10.1093/bioinformatics/btm388
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发表时间：
2008-02-15
期刊：
影响因子：
5.8
通讯作者：
Swofford, David L.
中科院分区：
文献类型：
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作者：
Nylander, Johan A. A.;Wilgenbusch, James C.;Swofford, David L.
成功的马尔可夫链蒙特卡罗（MCMC）推理的关键因素是马尔可夫链的编程和运行性能。然而，MCMC模拟收敛诊断在遗传学中的明确使用质量评估仍然是罕见的。在这里，我们提出了一个简单的工具，使用MCMC模拟的输出和可视化的贝叶斯系统发育分析，如后验分裂概率和分支长度的收敛速度的主要利益的属性。系统发育MCMC模拟输出的图形探索提供了直观的，往往是关键的信息，分析的成功和可靠性。这里介绍的工具补充收敛诊断已经在其他软件包主要是为MCMC的其他应用程序设计。重要的是，使用单个参数或汇总统计量的迹线图的常见做法，例如采样树的似然分数，可能会误导评估系统发育MCMC模拟的成功。
A key element to a successful Markov chain Monte Carlo (MCMC) inference is the programming and run performance of the Markov chain. However, the explicit use of quality assessments of the MCMC simulationsconvergence diagnosticsin phylogenetics is still uncommon. Here, we present a simple tool that uses the output from MCMC simulations and visualizes a number of properties of primary interest in a Bayesian phylogenetic analysis, such as convergence rates of posterior split probabilities and branch lengths. Graphical exploration of the output from phylogenetic MCMC simulations gives intuitive and often crucial information on the success and reliability of the analysis. The tool presented here complements convergence diagnostics already available in other software packages primarily designed for other applications of MCMC. Importantly, the common practice of using trace-plots of a single parameter or summary statistic, such as the likelihood score of sampled trees, can be misleading for assessing the success of a phylogenetic MCMC simulation.