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Quartet-based phylogenetic inference: Improvements and limits

机译:基于四重奏的系统发育推断:改进和局限性

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摘要

We analyze the performance of quartet methods in phylogenetic reconstruction. These methods first compute four-taxon trees (4-trees) and then use a combinatorial algorithm to infer a phylogeny that respects the inferred 4-trees as much as possible. Quartet puzzling (QP) is one of the few methods able to take weighting of the 4-trees, which is inferred by maximum likelihood, into account. QP seems to be widely used. We present weight optimization (WO), a new algorithm which is also based on weighted 4-trees. WO is faster and offers better theoretical guarantees than QP. Moreover, computer simulations indicate that the topological accuracy of WO is less dependent on the shape of the correct tree. However, although the performance of WO is better overall than that of QP. it is still less efficient than traditional phylogenetic reconstruction approaches based on pairwise evolutionary distances or maximum likelihood. This is likely related to long-branch attraction, a phenomenon to which quartet methods are very sensitive, and to inappropriate use of the initial results (weights) obtained by maximum likelihood for every quartet.
机译:我们分析了四重奏方法在系统发育重建中的表现。这些方法首先计算四分类树(4树),然后使用组合算法来推断系统发育,尽可能地尊重推断的4树。四重奏谜题 (QP) 是为数不多的能够考虑 4 棵树加权的方法之一,这是通过最大似然推断的。QP似乎被广泛使用。我们提出了权重优化 (WO),这是一种基于加权 4 树的新算法。WO 比 QP 更快,并提供更好的理论保证。此外,计算机模拟表明,WO的拓扑精度对正确树形的依赖性较小。然而,虽然WO的整体表现优于QP。它仍然不如基于成对进化距离或最大似然的传统系统发育重建方法有效。这可能与长分支吸引有关,四重奏方法对这种现象非常敏感,并且不恰当地使用每个四重奏的最大似然获得的初始结果(权重)。

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