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完美分类群抽样与固定分类群可追溯性:引入一类分类群集的系统发育决定性集合。

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

作者信息

Fischer Mareike, Pott Janne

机构信息

Institute of Mathematics and Computer Science, University of Greifswald, Greifswald, Germany.

Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany.

出版信息

Bull Math Biol. 2025 Jun 10;87(7):94. doi: 10.1007/s11538-025-01457-7.

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.

摘要

分类群集合的系统发育决定性集合具有这样的特性

如果为其每个元素选择树,只要这些树是兼容的,那么得到的超树就是唯一的。这意味着只要描述(输入)物种集合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“完美分类群抽样”。对于有根树,判断给定的一组输入分类群集合是否具有系统发育决定性可以在多项式时间内完成,然而,确定一组分类群集合对于无根树是否具有系统发育决定性的判定问题不幸地是coNP完全问题,因此在实际中对于大型实例很难解决。这表明识别这样的集合通常很困难。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合,即所谓的固定分类群可追溯集合,它们被保证具有系统发育决定性,并且可以在多项式时间内识别。我们使用组合方法以及模拟,比较了固定分类群可追溯性和系统发育决定性的性质,例如,通过推导对于这些性质中每一个性质,输入集合中所需的四元组集合(即4元组的集合)数量的上下界。特别地,我们纠正了文献中关于系统发育决定性的一个错误的下界。我们已经在R语言中实现了确定给定的分类群集合是否是固定分类群可追溯的算法,并将我们的软件包FixingTaxonTraceR公开可用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b83c/12152082/e5923a6ab90c/11538_2025_1457_Fig1_HTML.jpg

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