Phylogenetic networks do not need to be complex: using fewer reticulations to represent conflicting clusters.

Phylogenetic networks do not need to be complex: using fewer reticulations to represent conflicting clusters.
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DOI:
10.1093/bioinformatics/btq202
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发表时间:
2010-06-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
通讯作者:
Huson D
Huson D
中科院分区:
其他
文献类型:
--
作者:
van Iersel L;Kelk S;Rupp R;Huson D

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系统发育树被广泛用来显示物种群体是如何进化的估计。每一棵系统发育树都可以被视为从共同祖先进化而来的物种的簇、亚群的集合。当为几个数据集(例如,不同基因)获得系统发育树时,它们的聚类往往是相互矛盾的。因此,这种数据集的所有簇的集合不能组合成单一的系统发育树。系统发育网络是系统发育树的泛化,可用于显示更复杂的进化史,包括网状事件,如杂交、重组和水平基因转移。在这里,我们提出了新的CASS算法,它可以将任何一组集群组合成一个系统发育网络。我们证明了用CASS方法构造的网络通常比用其他方法构造的网络简单。此外,我们还证明了只要存在这样的网络,CASS就能保证生成一个每个双连通分支至多有两个网状的网络。我们已经实现了CASS,并将其集成到免费提供的Dendroscope软件中。联系人:l.j.j.v.iersel@gmail.com补充信息:补充数据可在BioInformation Online上获得。
Phylogenetic trees are widely used to display estimates of how groups of species are evolved. Each phylogenetic tree can be seen as a collection of clusters, subgroups of the species that evolved from a common ancestor. When phylogenetic trees are obtained for several datasets (e.g. for different genes), then their clusters are often contradicting. Consequently, the set of all clusters of such a dataset cannot be combined into a single phylogenetic tree. Phylogenetic networks are a generalization of phylogenetic trees that can be used to display more complex evolutionary histories, including reticulate events, such as hybridizations, recombinations and horizontal gene transfers. Here, we present the new Cass algorithm that can combine any set of clusters into a phylogenetic network. We show that the networks constructed by Cass are usually simpler than networks constructed by other available methods. Moreover, we show that Cass is guaranteed to produce a network with at most two reticulations per biconnected component, whenever such a network exists. We have implemented Cass and integrated it into the freely available Dendroscope software. Contact: l.j.j.v.iersel@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
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