Novák Adám, Miklós István, Lyngsø Rune, Hein Jotun
Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG Oxford, UK.
Bioinformatics. 2008 Oct 15;24(20):2403-4. doi: 10.1093/bioinformatics/btn457. Epub 2008 Aug 27.
Bayesian analysis is one of the most popular methods in phylogenetic inference. The most commonly used methods fix a single multiple alignment and consider only substitutions as phylogenetically informative mutations, though alignments and phylogenies should be inferred jointly as insertions and deletions also carry informative signals. Methods addressing these issues have been developed only recently and there has not been so far a user-friendly program with a graphical interface that implements these methods.
We have developed an extendable software package in the Java programming language that samples from the joint posterior distribution of phylogenies, alignments and evolutionary parameters by applying the Markov chain Monte Carlo method. The package also offers tools for efficient on-the-fly summarization of the results. It has a graphical interface to configure, start and supervise the analysis, to track the status of the Markov chain and to save the results. The background model for insertions and deletions can be combined with any substitution model. It is easy to add new substitution models to the software package as plugins. The samples from the Markov chain can be summarized in several ways, and new postprocessing plugins may also be installed.
贝叶斯分析是系统发育推断中最流行的方法之一。最常用的方法固定单个多序列比对，并且仅将替换视为系统发育信息性突变，尽管比对和系统发育应该联合推断，因为插入和缺失也携带信息性信号。解决这些问题的方法直到最近才被开发出来，并且到目前为止还没有一个具有图形界面的用户友好程序来实现这些方法。
我们用Java编程语言开发了一个可扩展的软件包，通过应用马尔可夫链蒙特卡罗方法从系统发育、比对和进化参数的联合后验分布中进行采样。该软件包还提供了对结果进行高效即时总结的工具。它有一个图形界面来配置、启动和监督分析，跟踪马尔可夫链的状态并保存结果。插入和缺失的背景模型可以与任何替换模型相结合。作为插件，很容易将新的替换模型添加到软件包中。来自马尔可夫链的样本可以通过多种方式进行总结，并且也可以安装新的后处理插件。
