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Consensus properties for the deep coalescence problem and their application for scalable tree search

机译:深度合并问题的共识属性及其在可伸缩树搜索中的应用

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摘要

BackgroundTo infer a species phylogeny from unlinked genes, phylogenetic inference methods must confront the biological processes that create incongruence between gene trees and the species phylogeny. Intra-specific gene variation in ancestral species can result in deep coalescence, also known as incomplete lineage sorting, which creates incongruence between gene trees and the species tree. One approach to account for deep coalescence in phylogenetic analyses is the deep coalescence problem, which takes a collection of gene trees and seeks the species tree that implies the fewest deep coalescence events. Although this approach is promising for phylogenetics, the consensus properties of this problem are mostly unknown and analyses of large data sets may be computationally prohibitive.
机译:背景技术为了从未关联的基因推断出物种系统发育,系统发育推断方法必须面对在基因树与物种系统发育之间产生不一致的生物学过程。祖先物种中的特定物种内基因变异会导致深度合并,也称为不完整的谱系排序,这会在基因树和物种树之间产生不一致。解决系统发育分析中的深聚结的一种方法是深聚结问题,该问题需要收集基因树并寻找隐含最少深聚结事件的物种树。尽管这种方法在系统发育研究中很有前途,但该问题的共识性质几乎是未知的,并且对大数据集的分析可能在计算上令人望而却步。

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