Department of Computer Science, University of Tuebingen, 72076 Tuebingen, Germany.
IEEE/ACM Trans Comput Biol Bioinform. 2013 Jan-Feb;10(1):61-72. doi: 10.1109/TCBB.2012.133.
In the minimizing-deep-coalescences (MDC) approach for species tree inference, a tree that has the minimal deep coalescence cost for reconciling a collection of gene trees is taken as an estimate of the species tree topology. The MDC method possesses the desirable Pareto property, and in practice it is quite accurate and computationally efficient. Here, in order to better understand the MDC method, we investigate some properties of the deep coalescence cost. We prove that the unit neighborhood of either a rooted species tree or a rooted gene tree under the deep coalescence cost is exactly the same as the tree's unit neighborhood under the rooted nearest-neighbor interchange (NNI) distance. Next, for a fixed species tree, we obtain the maximum deep coalescence cost across all gene trees as well as the number of gene trees that achieve the maximum cost. We also study corresponding problems for a fixed gene tree.
在用于物种树推断的最小深度融合(MDC)方法中,选择具有最小深度融合代价的树作为物种树拓扑结构的估计值,该代价用于协调一组基因树。MDC 方法具有理想的帕累托特性,在实践中它非常准确且计算效率高。在这里,为了更好地理解 MDC 方法,我们研究了深度融合代价的一些性质。我们证明,在深度融合代价下,无论是有根物种树还是有根基因树的单位邻域,都与根最近邻居交换(NNI)距离下的树的单位邻域完全相同。接下来,对于固定的物种树,我们获得了所有基因树的最大深度融合代价以及达到最大代价的基因树的数量。我们还研究了固定基因树的对应问题。