Lefort Vincent, Longueville Jean-Emmanuel, Gascuel Olivier
Institut de Biologie Computationnelle, LIRMM, UMR 5506 - CNRS et Université de Montpellier, Montpellier, France.
Unité de Bioinformatique Evolutive, C3BI, USR 3756 - Institut Pasteur et CNRS, Paris, France.
Mol Biol Evol. 2017 Sep 1;34(9):2422-2424. doi: 10.1093/molbev/msx149.
Model selection using likelihood-based criteria (e.g., AIC) is one of the first steps in phylogenetic analysis. One must select both a substitution matrix and a model for rates across sites. A simple method is to test all combinations and select the best one. We describe heuristics to avoid these extensive calculations. Runtime is divided by ∼2 with results remaining nearly the same, and the method performs well compared with ProtTest and jModelTest2. Our software, "Smart Model Selection" (SMS), is implemented in the PhyML environment and available using two interfaces: command-line (to be integrated in pipelines) and a web server (http://www.atgc-montpellier.fr/phyml-sms/).
使用基于似然性的标准（如AIC）进行模型选择是系统发育分析的首要步骤之一。必须同时选择一个替换矩阵和一个位点速率模型。一种简单的方法是测试所有组合并选择最佳组合。我们描述了一些启发式方法以避免这些大量计算。运行时间大约减半，结果基本保持不变，并且与ProtTest和jModelTest2相比，该方法表现良好。我们的软件“智能模型选择”（SMS）在PhyML环境中实现，并通过两个接口可用：命令行（将集成到管道中）和网络服务器（http://www.atgc-montpellier.fr/phyml-sms/）。
