Computational Evolution Group, University of Auckland, Auckland, New Zealand.
Mol Biol Evol. 2012 Feb;29(2):751-61. doi: 10.1093/molbev/msr232. Epub 2011 Sep 22.
We describe a procedure for model averaging of relaxed molecular clock models in Bayesian phylogenetics. Our approach allows us to model the distribution of rates of substitution across branches, averaged over a set of models, rather than conditioned on a single model. We implement this procedure and test it on simulated data to show that our method can accurately recover the true underlying distribution of rates. We applied the method to a set of alignments taken from a data set of 12 mammalian species and uncovered evidence that lognormally distributed rates better describe this data set than do exponentially distributed rates. Additionally, our implementation of model averaging permits accurate calculation of the Bayes factor(s) between two or more relaxed molecular clock models. Finally, we introduce a new computational approach for sampling rates of substitution across branches that improves the convergence of our Markov chain Monte Carlo algorithms in this context. Our methods are implemented under the BEAST 1.6 software package, available at http://beast-mcmc.googlecode.com.
我们描述了一种在贝叶斯系统发生学中对放松分子钟模型进行模型平均的方法。我们的方法允许我们对跨越支系的替代率分布进行建模，而不是对单个模型进行建模。我们实现了这种方法，并在模拟数据上进行了测试，结果表明我们的方法可以准确地恢复真实的替代率分布。我们将该方法应用于一组从 12 种哺乳动物数据集中提取的比对中，结果表明对数正态分布的替代率比指数分布的替代率更能描述该数据集。此外，我们的模型平均实现允许准确计算两个或更多放松分子钟模型之间的贝叶斯因子。最后，我们引入了一种新的计算跨支系替代率的方法，该方法提高了我们在这种情况下的马尔可夫链蒙特卡罗算法的收敛速度。我们的方法在 BEAST 1.6 软件包中实现，可在 http://beast-mcmc.googlecode.com 获得。
