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Linear-Time Algorithms for Some Phylogenetic Tree Completion Problems Under Robinson-Foulds Distance

机译:Robinson-Foulds距离下某些系统发育树完成问题的线性时间算法

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We consider two fundamental computational problems that arise when comparing phylogenetic trees, rooted or unrooted, with non-identical leaf sets. The first problem arises when comparing two trees where the leaf set of one tree is a proper subset of the other. The second problem arises when the two trees to be compared have only partially overlapping leaf sets. The traditional approach to handling these problems is to first restrict the two trees to their common leaf set. An alternative approach that has shown promise is to first complete the trees by adding missing leaves, so that the resulting trees have identical leaf sets. This requires the computation of an optimal completion that minimizes the distance between the two resulting trees over all possible completions. We provide optimal linear-time algorithms for both completion problems under the widely-used Robinson-Foulds (RF) distance measure. Our algorithm for the first problem improves the time complexity of the current fastest algorithm from quadratic (in the size of the two trees) to linear. No algorithms have yet been proposed for the more general second problem where both trees have missing leaves. We advance the study of this general problem by proposing a biologically meaningful restricted version of the general problem and providing optimal linear-time algorithms for the restricted version. Our experimental results on biological data sets suggest that using completion-based RF distances can result in different evolutionary inferences compared to traditional RF distances.
机译:当比较系统树(有根或无根)与不相同的叶集时,我们考虑了两个基本的计算问题。当比较两棵树时第一个问题出现,其中一棵树的叶子集是另一棵树的适当子集。当要比较的两棵树仅具有部分重叠的叶集时,出现第二个问题。解决这些问题的传统方法是首先将两棵树限制为它们的公共叶集。一个有希望的替代方法是通过添加缺少的叶子来首先完成树木的构建,以使生成的树木具有相同的叶子集。这需要计算最佳完成度,该最佳完成度会在所有可能的完成度上最小化两个结果树之间的距离。在广泛使用的Robinson-Foulds(RF)距离测度下,我们为两个完井问题都提供了最佳的线性时间算法。我们针对第一个问题的算法将当前最快算法的时间复杂度从二次(在两棵树的大小上)提高到了线性。对于两棵树都缺少叶子的更普遍的第二个问题,尚未提出算法。通过提出一般问题的生物学意义上的受限版本并为受限版本提供最佳线性时间算法,我们推进了对这一通用问题的研究。我们在生物学数据集上的实验结果表明,与传统的RF距离相比,使用基于完成度的RF距离可以导致不同的进化推论。

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