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PhySIC:一种具有理想属性的否决超树方法。

PhySIC: a veto supertree method with desirable properties.

作者信息

Ranwez Vincent, Berry Vincent, Criscuolo Alexis, Fabre Pierre-Henri, Guillemot Sylvain, Scornavacca Celine, Douzery Emmanuel J P

机构信息

Institut des Sciences de l'Evolution (ISEM, UMR 5554 CNRS), Université Montpellier II, Montpellier, Cedex 5, France.

出版信息

Syst Biol. 2007 Oct;56(5):798-817. doi: 10.1080/10635150701639754.

Abstract

This paper focuses on veto supertree methods; i.e., methods that aim at producing a conservative synthesis of the relationships agreed upon by all source trees. We propose desirable properties that a supertree should satisfy in this framework, namely the non-contradiction property (PC) and the induction property (PI). The former requires that the supertree does not contain relationships that contradict one or a combination of the source topologies, whereas the latter requires that all topological information contained in the supertree is present in a source tree or collectively induced by several source trees. We provide simple examples to illustrate their relevance and that allow a comparison with previously advocated properties. We show that these properties can be checked in polynomial time for any given rooted supertree. Moreover, we introduce the PhySIC method (PHYlogenetic Signal with Induction and non-Contradiction). For k input trees spanning a set of n taxa, this method produces a supertree that satisfies the above-mentioned properties in O(kn(3) + n(4)) computing time. The polytomies of the produced supertree are also tagged by labels indicating areas of conflict as well as those with insufficient overlap. As a whole, PhySIC enables the user to quickly summarize consensual information of a set of trees and localize groups of taxa for which the data require consolidation. Lastly, we illustrate the behaviour of PhySIC on primate data sets of various sizes, and propose a supertree covering 95% of all primate extant genera. The PhySIC algorithm is available at http://atgc.lirmm.fr/cgi-bin/PhySIC.

摘要

本文聚焦于否决超树方法,即旨在对所有源树所达成的关系进行保守综合的方法。我们提出了在此框架下超树应满足的理想属性,即无矛盾属性(PC)和归纳属性(PI)。前者要求超树不包含与源拓扑结构之一或其组合相矛盾的关系,而后者要求超树中包含的所有拓扑信息都存在于一棵源树中或由几棵源树共同归纳得出。我们提供了简单示例来说明它们的相关性,并能与先前倡导的属性进行比较。我们表明,对于任何给定的有根超树,这些属性都可以在多项式时间内进行检查。此外,我们引入了PhySIC方法(具有归纳和无矛盾性的系统发育信号)。对于跨越一组n个分类单元的k棵输入树,该方法在O(kn(3) + n(4))的计算时间内生成一棵满足上述属性的超树。所生成超树的多歧分支也会被标记,标签指示冲突区域以及重叠不足的区域。总体而言,PhySIC能让用户快速总结一组树的共识信息,并定位数据需要整合的分类单元组。最后,我们展示了PhySIC在各种规模的灵长类数据集上表现,并提出了一棵覆盖所有现存灵长类属95%的超树。PhySIC算法可在http://atgc.lirmm.fr/cgi-bin/PhySIC获取。

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