Perfect Taxon Sampling and Fixing Taxon Traceability: Introducing a Class of Phylogenetically Decisive Collections of Taxon Sets.

IF 2 4区 数学 Q2 BIOLOGY
Mareike Fischer, Janne Pott
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引用次数: 0

Abstract

Phylogenetically decisive collections of taxon sets have the property that if trees are chosen for each of their elements, as long as these trees are compatible, the resulting supertree is unique. This means that as long as the trees describing the phylogenetic relationships of the (input) species sets are compatible, they can only be combined into a common supertree in precisely one way. This setting is sometimes also referred to as "perfect taxon sampling". While for rooted trees, the decision if a given set of input taxon sets is phylogenetically decisive can be made in polynomial time, the decision problem to determine whether a collection of taxon sets is phylogenetically decisive concerning unrooted trees is unfortunately coNP-complete and therefore in practice hard to solve for large instances. This shows that recognizing such sets is often difficult. In this paper, we explain phylogenetic decisiveness and introduce a class of input taxon sets, namely so-called fixing taxon traceable sets, which are guaranteed to be phylogenetically decisive and which can be recognized in polynomial time. Using both combinatorial approaches as well as simulations, we compare properties of fixing taxon traceability and phylogenetic decisiveness, e.g., by deriving lower and upper bounds for the number of quadruple sets (i.e., sets of 4-tuples) needed in the input set for each of these properties. In particular, we correct an erroneous lower bound concerning phylogenetic decisiveness from the literature. We have implemented the algorithm to determine if a given collection of taxon sets is fixing taxon traceable in R and made our software package FixingTaxonTraceR publicly available.

完善的分类群采样和固定分类群溯源性:引入一类系统发育决定性的分类群集合。
系统发育决定性的分类群集合具有这样的特性:如果为每个元素选择树,只要这些树是兼容的,那么最终的超树就是唯一的。这意味着,只要描述(输入)物种集的系统发育关系的树是兼容的,它们就只能以一种精确的方式组合成一个共同的超树。这种设置有时也被称为“完美的分类群采样”。而对于有根树来说,一组给定的输入分类群集是否具有系统发育决定性的决策可以在多项式时间内做出,而对于无根树来说,确定一组分类群集是否具有系统发育决定性的决策问题不幸是conp完全的,因此在实践中很难解决大型实例。这表明识别这样的集合通常是困难的。在本文中,我们解释了系统发育决定性,并引入了一类输入分类群集,即所谓的固定分类群可追溯集,它保证是系统发育决定性的,并且可以在多项式时间内识别。使用组合方法和模拟,我们比较了固定分类群可追溯性和系统发育决定性的特性,例如,通过推导输入集中需要的四元组(即4元组的集合)数量的下界和上界。特别是,我们从文献中修正了一个关于系统发育决定性的错误下界。我们已经在R中实现了一种算法来确定给定的分类集集合是否具有固定分类单元可追溯性,并公开了我们的软件包FixingTaxonTraceR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.90
自引率
8.60%
发文量
123
审稿时长
7.5 months
期刊介绍: The Bulletin of Mathematical Biology, the official journal of the Society for Mathematical Biology, disseminates original research findings and other information relevant to the interface of biology and the mathematical sciences. Contributions should have relevance to both fields. In order to accommodate the broad scope of new developments, the journal accepts a variety of contributions, including: Original research articles focused on new biological insights gained with the help of tools from the mathematical sciences or new mathematical tools and methods with demonstrated applicability to biological investigations Research in mathematical biology education Reviews Commentaries Perspectives, and contributions that discuss issues important to the profession All contributions are peer-reviewed.
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