STEM：在溯祖模型下使用最大似然法进行基因树物种树估计。
STEM: species tree estimation using maximum likelihood for gene trees under coalescence.
作者信息
Kubatko Laura S, Carstens Bryan C, Knowles L Lacey
机构信息
Departments of Statistics and Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA.
出版信息
Bioinformatics. 2009 Apr 1;25(7):971-3. doi: 10.1093/bioinformatics/btp079. Epub 2009 Feb 10.
UNLABELLED
STEM is a software package written in the C language to obtain maximum likelihood (ML) estimates for phylogenetic species trees given a sample of gene trees under the coalescent model. It includes options to compute the ML species tree, search the space of all species trees for the k trees of highest likelihood and compute ML branch lengths for a user-input species tree.
AVAILABILITY
The STEM package, including source code, is freely available at http://www.stat.osu.edu/~lkubatko/software/STEM/.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
未标注
STEM是一个用C语言编写的软件包，用于在合并模型下给定基因树样本时获得系统发育物种树的最大似然（ML）估计。它包括计算ML物种树、在所有物种树的空间中搜索k个似然最高的树以及为用户输入的物种树计算ML分支长度的选项。
可用性
STEM软件包，包括源代码，可在http://www.stat.osu.edu/~lkubatko/software/STEM/免费获取。
补充信息
补充数据可在《生物信息学》在线获取。
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