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使用边并网络比较和展示系统发育树。

Comparing and displaying phylogenetic trees using edge union networks.

作者信息

Miyagi Miriam, Wheeler Ward C

机构信息

Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford St, Cambridge, MA, 02138, USA.

Division of Invertebrate Zoology, American Museum of Natural History, 200 Central Park West, New York, NY, 10024-5192, USA.

出版信息

Cladistics. 2019 Dec;35(6):688-694. doi: 10.1111/cla.12374. Epub 2019 Mar 5.

Abstract

The general problem of representing collections of trees as a single graph has led to many tree summary techniques. Many consensus approaches take sets of trees (either inferred as separate gene trees or gleaned from the posterior of a Bayesian analysis) and produce a single "best" tree. In scenarios where horizontal gene transfer or hybridization are suspected, networks may be preferred, which allow for nodes to have two parents, representing the fusion of lineages. One such construct is the cluster union network (CUN), which is constructed using the union of all clusters in the input trees. The CUN has a number of mathematically desirable properties, but can also present edges not observed in the input trees. In this paper we define a new network construction, the edge union network (EUN), which displays edges if and only if they are contained in the input trees. We also demonstrate that this object can be constructed with polynomial time complexity given arbitrary phylogenetic input trees, and so can be used in conjunction with network analysis techniques for further phylogenetic hypothesis testing.

摘要

将树的集合表示为单个图的一般问题催生了许多树总结技术。许多共识方法采用树的集合(要么作为单独的基因树推断得出,要么从贝叶斯分析的后验中收集),并生成一棵单一的“最佳”树。在怀疑存在水平基因转移或杂交的情况下,网络可能更受青睐,因为网络允许节点有两个父节点,代表谱系的融合。一种这样的结构是簇并网络(CUN),它是使用输入树中所有簇的并集构建的。CUN具有许多数学上理想的属性,但也可能呈现出输入树中未观察到的边。在本文中,我们定义了一种新的网络构建方法,即边并网络(EUN),它当且仅当边包含在输入树中时才显示这些边。我们还证明,给定任意系统发育输入树,这个对象可以在多项式时间复杂度内构建,因此可以与网络分析技术结合使用,以进行进一步的系统发育假设检验。

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