Accurate Model Selection of Relaxed Molecular Clocks in Bayesian Phylogenetics
Accurate Model Selection of Relaxed Molecular Clocks in Bayesian Phylogenetics
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DOI：
10.1093/molbev/mss243
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发表时间：
2013-02-01
影响因子：
10.7
通讯作者：
Lemey, Philippe
中科院分区：
文献类型：
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作者：
Baele, Guy;Li, Wai Lok Sibon;Lemey, Philippe
最近实施的路径采样（PS）和垫脚石采样（SS）已被证明优于谐波均值估计（HME）和后验模拟的模拟赤池的信息标准，通过马尔可夫链蒙特卡罗（AICM），在人口和分子时钟模型的贝叶斯模型选择。几乎同时，贝叶斯模型的平均方法，避免了一个单一的模型，但平均超过一组宽松的时钟模型的条件。该方法返回每个时钟模型的后验概率的估计，通过该估计，可以估计有利于最大后验（MAP）时钟模型的贝叶斯因子;然而，当MAP模型的后验概率接近1时，该贝叶斯因子估计可能会受到影响。在这里，我们比较这两个最近的发展与HME，稳定/平滑HME（sHME），和AICM，使用合成和经验数据。我们的比较结果表明，MAP识别及其贝叶斯因子提供了与PS和SS相似的性能，并且这些方法在选择正确的底层时钟模型方面大大优于HME，sHME和AICM。我们还说明了使用适当的先验的经验数据集的大集合的重要性。
Recent implementations of path sampling (PS) and stepping-stone sampling (SS) have been shown to outperform the harmonic mean estimator (HME) and a posterior simulation-based analog of Akaike's information criterion through Markov chain Monte Carlo (AICM), in Bayesian model selection of demographic and molecular clock models. Almost simultaneously, a Bayesian model averaging approach was developed that avoids conditioning on a single model but averages over a set of relaxed clock models. This approach returns estimates of the posterior probability of each clock model through which one can estimate the Bayes factor in favor of the maximum a posteriori (MAP) clock model; however, this Bayes factor estimate may suffer when the posterior probability of the MAP model approaches 1. Here, we compare these two recent developments with the HME, stabilized/smoothed HME (sHME), and AICM, using both synthetic and empirical data. Our comparison shows reassuringly that MAP identification and its Bayes factor provide similar performance to PS and SS and that these approaches considerably outperform HME, sHME, and AICM in selecting the correct underlying clock model. We also illustrate the importance of using proper priors on a large set of empirical data sets.