arXiv 2107.096962021-07-20q-bio.PE

系统发生一致性网络：计算1-嵌套系统发生网络的一致性

Phylogenetic consensus networks: Computing a consensus of 1-nested phylogenetic networks

Katharina T. Huber, Vincent Moulton, Andreas Spillner

摘要：

计算一个\emph{consensus tree}以总结一系列有根系统发育树的共同特征是系统发育遗传学中一个重要且研究得很好的问题，所有的叶子集合都被同一个物种集合X双射标记。然而，最近，它已成为兴趣，找到一个更一般的，根有向无环图的集合的所有的sink集双射标记的~（X），所谓的有根\emph{phylogenetic networks}的共识。这些网络用于分析相互交叉的物种的进化，例如植物和病毒。在本文中，我们介绍了一种算法，用于计算一个所谓的1- \emph{nested}系统发育网络的集合的共识。我们的方法建立在Roselló等人之前的结果之上。该结果描述了任何1-嵌套系统发育网络的编码，即（X）的子集的有序对的集合。更具体地说，我们描述了作为某些1-嵌套系统发育网络的编码而出现的有序对的集合，然后使用这个特征来计算$O(t|X|^2+|X|^3)$时间内~ $t$ 1-嵌套网络集合的\emph{consensus network}。将我们的算法应用到一组系统发育树上，得到了著名的多数规则共识树。我们的方法为未来的工作带来了几个新的方向，我们希望它能提供一个有用的新工具来帮助理解复杂的进化场景。

英文摘要：

An important and well-studied problem in phylogenetics is to compute a \emph{consensus tree} so as to summarize the common features within a collection of rooted phylogenetic trees, all whose leaf-sets are bijectively labeled by the same set~(X) of species. More recently, however, it has become of interest to find a consensus for a collection of more general, rooted directed acyclic graphs all of whose sink-sets are bijectively labeled by~(X), so called rooted \emph{phylogenetic networks}. These networks are used to analyse the evolution of species that cross with one another, such as plants and viruses. In this paper, we introduce an algorithm for computing a consensus for a collection of so-called 1-\emph{nested} phylogenetic networks. Our approach builds on a previous result by Roselló et al. that describes an encoding for any 1-nested phylogenetic network in terms of a collection of ordered pairs of subsets of (X).More specifically, we characterize those collections of ordered pairs that arise as the encoding of some 1-nested phylogenetic network, and then use this characterization to compute a \emph{consensus network} for a collection of~$t$ 1-nested networks in $O(t|X|^2+|X|^3)$ time. Applying our algorithm to a collection of phylogenetic trees yields the well-known majority rule consensus tree. Our approach leads to several new directions for futurework, and we expect that it should provide a useful new tool to help understand complex evolutionary scenarios.

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英文摘要：

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