Soria-Carrasco Víctor, Talavera Gerard, Igea Javier, Castresana Jose
Department of Physiology and Molecular Biodiversity, Institute of Molecular Biology of Barcelona, CSIC, Jordi Girona 18, 08034 Barcelona, Spain.
Bioinformatics. 2007 Nov 1;23(21):2954-6. doi: 10.1093/bioinformatics/btm466. Epub 2007 Sep 22.
We introduce a new phylogenetic comparison method that measures overall differences in the relative branch length and topology of two phylogenetic trees. To do this, the algorithm first scales one of the trees to have a global divergence as similar as possible to the other tree. Then, the branch length distance, which takes differences in topology and branch lengths into account, is applied to the two trees. We thus obtain the minimum branch length distance or K tree score. Two trees with very different relative branch lengths get a high K score whereas two trees that follow a similar among-lineage rate variation get a low score, regardless of the overall rates in both trees. There are several applications of the K tree score, two of which are explained here in more detail. First, this score allows the evaluation of the performance of phylogenetic algorithms, not only with respect to their topological accuracy, but also with respect to the reproduction of a given branch length variation. In a second example, we show how the K score allows the selection of orthologous genes by choosing those that better follow the overall shape of a given reference tree.
我们介绍了一种新的系统发育比较方法，该方法可测量两棵系统发育树在相对分支长度和拓扑结构上的总体差异。为此，该算法首先对其中一棵树进行缩放，使其全局分歧尽可能与另一棵树相似。然后，将同时考虑拓扑结构和分支长度差异的分支长度距离应用于这两棵树。由此我们得到最小分支长度距离或K树得分。相对分支长度差异很大的两棵树会得到较高的K得分，而谱系间速率变化相似的两棵树则会得到较低的得分，无论两棵树的总体速率如何。K树得分有多种应用，这里详细解释其中两种。首先，该得分不仅可以评估系统发育算法在拓扑准确性方面的性能，还可以评估其在再现给定分支长度变化方面的性能。在第二个例子中，我们展示了K得分如何通过选择那些更符合给定参考树总体形状的基因来选择直系同源基因。
