Department of Computer Science, University of Otago, Dunedin, New Zealand.
Institute of Mathematics and Computer Science, University of Greifswald, Greifswald, Germany.
J Math Biol. 2021 Nov 5;83(5):60. doi: 10.1007/s00285-021-01685-0.
In many phylogenetic applications, such as cancer and virus evolution, time trees, evolutionary histories where speciation events are timed, are inferred. Of particular interest are clock-like trees, where all leaves are sampled at the same time and have equal distance to the root. One popular approach to model clock-like trees is coalescent theory, which is used in various tree inference software packages. Methodologically, phylogenetic inference methods require a tree space over which the inference is performed, and the geometry of this space plays an important role in statistical and computational aspects of tree inference algorithms. It has recently been shown that coalescent tree spaces possess a unique geometry, different from that of classical phylogenetic tree spaces. Here we introduce and study a space of discrete coalescent trees. They assume that time is discrete, which is natural in many computational applications. This tree space is a generalisation of the previously studied ranked nearest neighbour interchange space, and is built upon tree-rearrangement operations. We generalise existing results about ranked trees, including an algorithm for computing distances in polynomial time, and in particular provide new results for both the space of discrete coalescent trees and the space of ranked trees. We establish several geometrical properties of these spaces and show how these properties impact various algorithms used in phylogenetic analyses. Our tree space is a discretisation of a previously introduced time tree space, called t-space, and hence our results can be used to approximate solutions to various open problems in t-space.
在许多系统发育应用中,如癌症和病毒进化,推断出时间树,即物种形成事件定时的进化历史。特别感兴趣的是类似钟的树,其中所有叶子都在同一时间被采样,并且与根的距离相等。一种流行的模拟类似钟的树的方法是合并理论,它被用于各种树推断软件包中。从方法论上讲,系统发育推断方法需要一个树空间来进行推断,这个空间的几何形状在树推断算法的统计和计算方面起着重要作用。最近有人指出,合并树空间具有独特的几何形状,与经典的系统发育树空间不同。在这里,我们引入并研究了离散合并树的空间。它们假设时间是离散的,这在许多计算应用中是很自然的。这个树空间是以前研究过的排名最近邻居交换空间的推广,并且是基于树重排操作构建的。我们推广了关于排名树的现有结果,包括一种在多项式时间内计算距离的算法,特别是为离散合并树空间和排名树空间提供了新的结果。我们建立了这些空间的几个几何性质,并展示了这些性质如何影响系统发育分析中使用的各种算法。我们的树空间是以前引入的时间树空间 t-space 的离散化,因此我们的结果可用于近似 t-space 中各种开放问题的解。