Redelings Benjamin D
Biology Department, Duke University, Durham, NC 27708, USA.
Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA.
Bioinformatics. 2021 Sep 29;37(18):3032-3034. doi: 10.1093/bioinformatics/btab129.
We describe improvements to BAli-Phy, a Markov chain Monte Carlo (MCMC) program that jointly estimates phylogeny, alignment and other parameters from unaligned sequence data. Version 3 is substantially faster for large trees, and implements covarion models, additional codon models and other new models. It implements ancestral state reconstruction, allows prior selection for all model parameters, and can also analyze multiple genes simultaneously.
Software is available for download at http://www.bali-phy.org. C++ source code is freely available on Github under the GPL2 License.
Supplementary data are available at Bioinformatics online.
我们描述了对BAli-Phy的改进，这是一个马尔可夫链蒙特卡罗（MCMC）程序，可从未比对的序列数据中联合估计系统发育、比对和其他参数。版本3对于大型树的速度大幅提升，并实现了协变模型、额外的密码子模型和其他新模型。它实现了祖先状态重建，允许对所有模型参数进行先验选择，并且还可以同时分析多个基因。
软件可从http://www.bali-phy.org下载。C++源代码在GPL2许可下可在Github上免费获取。
补充数据可在《生物信息学》在线版获取。
