bModelTest: Bayesian phylogenetic site model averaging and model comparison.
bModelTest: Bayesian phylogenetic site model averaging and model comparison.
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DOI：
10.1186/s12862-017-0890-6
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发表时间：
2017-02-06
影响因子：
3.4
通讯作者：
Drummond AJ
中科院分区：
文献类型：
--
作者：
Bouckaert RR;Drummond AJ
通过贝叶斯方法重建系统发育有很多好处，包括提供一个数学上合理的框架，提供对不确定性的现实估计，以及能够基于形式原则整合不同来源的信息。贝叶斯系统发育分析在解释核苷酸序列数据方面很受欢迎，但是对于这样的研究，需要指定一个位点模型和相关的替代模型。通常情况下，站点模型的参数是不重要的，并且使用特别的或附加的基于可能性的分析来选择单个站点模型。bModelTest允许贝叶斯方法在系统发育分析中推断和边缘化位点模型。它基于跨维马尔可夫链蒙特卡罗（MCMC）建议，允许在替代模型之间切换，以及估计伽玛分布速率异质性的后验概率，不变位点的比例和不相等基频。该模型可以与核苷酸的全套时间可逆模型一起使用，但我们也介绍并演示了两个时间可逆替代模型子集的使用。使用这种新方法，可以在MCMC分析期间推断（和边缘化）站点模型，而不需要预先确定，就像现在在实践中经常使用的基于可能性的方法一样。该方法在流行的BEAST 2软件的bModelTest包中实现，该软件是开源的，在GNU Lesser General Public License下许可，允许在广泛的模型下进行联合站点模型和树推理。本文的在线版本（doi:10.1186/s12862-017-0890-6）包含补充材料，可供授权用户使用。
Reconstructing phylogenies through Bayesian methods has many benefits, which include providing a mathematically sound framework, providing realistic estimates of uncertainty and being able to incorporate different sources of information based on formal principles. Bayesian phylogenetic analyses are popular for interpreting nucleotide sequence data, however for such studies one needs to specify a site model and associated substitution model. Often, the parameters of the site model is of no interest and an ad-hoc or additional likelihood based analysis is used to select a single site model. bModelTest allows for a Bayesian approach to inferring and marginalizing site models in a phylogenetic analysis. It is based on trans-dimensional Markov chain Monte Carlo (MCMC) proposals that allow switching between substitution models as well as estimating the posterior probability for gamma-distributed rate heterogeneity, a proportion of invariable sites and unequal base frequencies. The model can be used with the full set of time-reversible models on nucleotides, but we also introduce and demonstrate the use of two subsets of time-reversible substitution models. With the new method the site model can be inferred (and marginalized) during the MCMC analysis and does not need to be pre-determined, as is now often the case in practice, by likelihood-based methods. The method is implemented in the bModelTest package of the popular BEAST 2 software, which is open source, licensed under the GNU Lesser General Public License and allows joint site model and tree inference under a wide range of models. The online version of this article (doi:10.1186/s12862-017-0890-6) contains supplementary material, which is available to authorized users.