Gentrius: Generating Trees Compatible With a Set of Unrooted Subtrees and its Application to Phylogenetic Terraces.

IF 11 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Olga Chernomor, Christiane Elgert, Arndt von Haeseler
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引用次数: 0

Abstract

For a set of binary unrooted subtrees generating all binary unrooted trees compatible with them, i.e. generating their stand, is one of the classical problems in phylogenetics. Here, we introduce Gentrius-an efficient algorithm to tackle this task. The algorithm has a direct application in practice. Namely, Gentrius generates phylogenetic terraces-topologically distinct, equally scoring trees due to missing data. Despite stand generation being computationally intractable, we showed on simulated and biological datasets that Gentrius generates stands with millions of trees in feasible time. We exemplify that depending on the distribution of missing data across species and loci and the inferred phylogeny, the number of equally optimal terrace trees varies tremendously. The strict consensus tree computed from them displays all the branches unaffected by the pattern of missing data. Thus, by solving the problem of stand generation, in practice Gentrius provides an important systematic assessment of phylogenetic trees inferred from incomplete data. Furthermore, Gentrius can aid theoretical research by fostering understanding of tree space structure imposed by missing data.

Gentrius:生成与一组无根子树兼容的树及其在系统发育梯度中的应用。
对于一组二元无根子树,生成与之相容的所有二元无根树,即生成它们的立木,是系统发生学中的经典问题之一。在此,我们介绍一种高效算法 Gentrius 来解决这一问题。该算法可直接应用于实践。也就是说,Gentrius 可以生成系统发育阶梯--由于数据缺失而产生的拓扑不同、得分相同的树。尽管生成梯田在计算上很难,但我们在模拟和生物数据集上证明,Gentrius 能在可行的时间内生成数百万棵树的梯田。我们举例说明,根据缺失数据在物种和位点间的分布情况以及推断的系统发育情况,同样最优的台地树的数量会有巨大的差异。由它们计算出的严格共识树显示所有分支都不受缺失数据模式的影响。因此,在实践中,通过解决分支生成问题,Gentrius 可以对根据不完整数据推断出的系统发生树进行重要的系统评估。此外,Gentrius 还能帮助理论研究,促进对缺失数据所造成的树空间结构的理解。
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来源期刊
Molecular biology and evolution
Molecular biology and evolution 生物-进化生物学
CiteScore
19.70
自引率
3.70%
发文量
257
审稿时长
1 months
期刊介绍: Molecular Biology and Evolution Journal Overview: Publishes research at the interface of molecular (including genomics) and evolutionary biology Considers manuscripts containing patterns, processes, and predictions at all levels of organization: population, taxonomic, functional, and phenotypic Interested in fundamental discoveries, new and improved methods, resources, technologies, and theories advancing evolutionary research Publishes balanced reviews of recent developments in genome evolution and forward-looking perspectives suggesting future directions in molecular evolution applications.
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