phylogenetics with
phylogenetics with
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发表时间：
2012
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通讯作者：
Sudhir Kumar;A. Drummond;M. Suchard;Dong Xie;A. Rambaut
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作者：
Sudhir Kumar;A. Drummond;M. Suchard;Dong Xie;A. Rambaut
计算进化生物学、统计遗传学和基于聚结的群体遗传学对于分析和理解分子序列数据正变得越来越重要。我们提出了贝叶斯进化分析抽样树（BEAST）软件包版本1.7，它实现了一个家庭的马尔可夫链蒙特卡罗（MCMC）算法贝叶斯系统发育推断，分歧时间测定，结合分析，地理学，和相关的分子进化分析。该软件包包括一个增强的图形用户界面程序，称为贝叶斯进化分析实用程序（BEAUti），使访问分子序列和表型性状进化的高级模型，以前只提供给开发人员。该软件包还提供了新的工具，用于可视化和总结多物种合并和地理分析。BEAUti和BEAST 1.7是GNU Lesser通用公共许可证下的开源软件，可在http://beast-mcmc.googlecode.com和http://beast.bio.ed.ac.uk上获得。
Computational evolutionary biology, statistical phylogenetics, and coalescent-based population genetics are becoming increasingly central to the analysis and understanding of molecular sequence data. We present the Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7, which implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography, and related molecular evolutionary analyses. This package includes an enhanced graphical user interface program called Bayesian Evolutionary Analysis Utility (BEAUti) that enables access to advanced models for molecular sequence and phenotypic trait evolution that were previously available to developers only. The package also provides new tools for visualizing and summarizing multispecies coalescent and phylogeographic analyses. BEAUti and BEAST 1.7 are open source under the GNU lesser general public license and available at http://beast-mcmc.googlecode.com and http://beast.bio.ed.ac.uk.