Huson D H
FSPM, University of Bielefeld, Germany.
Bioinformatics. 1998;14(1):68-73. doi: 10.1093/bioinformatics/14.1.68.
Real evolutionary data often contain a number of different and sometimes conflicting phylogenetic signals, and thus do not always clearly support a unique tree. To address this problem, Bandelt and Dress (Adv. Math., 92, 47-05, 1992) developed the method of split decomposition. For ideal data, this method gives rise to a tree, whereas less ideal data are represented by a tree-like network that may indicate evidence for different and conflicting phylogenies.
SplitsTree is an interactive program, for analyzing and visualizing evolutionary data, that implements this approach. It also supports a number of distances transformations, the computation of parsimony splits, spectral analysis and bootstrapping.
真实的进化数据通常包含许多不同且有时相互冲突的系统发育信号,因此并不总是明确支持唯一的树状图。为了解决这个问题,班德尔特和德雷斯(《高等数学》,92卷,47 - 05页,1992年)开发了分裂分解方法。对于理想数据,该方法会生成一棵树,而不太理想的数据则由类似树状的网络表示,这可能表明存在不同且相互冲突的系统发育证据。
SplitsTree是一个用于分析和可视化进化数据的交互式程序,它实现了这种方法。它还支持多种距离变换、简约分裂的计算、光谱分析和自展法。