A Metric for Phylogenetic Trees Based on Matching

Lin, Yu; Rajan, Vaibhav; Moret, Bernard M. E.

doi:10.1007/978-3-642-21260-4_21

Cited by 63 publications

(69 citation statements)

References 16 publications

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“…For these reasons various metrics have been developed for comparing phylogenetic trees, see e.g. [1,2,4,9,15,16,18,19]. These metrics have different properties which can make them more (or less!)…”

Section: Introductionmentioning

confidence: 99%

A parsimony-based metric for phylogenetic trees

Moulton

2015

Advances in Applied Mathematics

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In evolutionary biology various metrics have been defined and studied for comparing phylogenetic trees. Such metrics are used, for example, to compare competing evolutionary hypotheses or to help organize algorithms that search for optimal trees. Here we introduce a new metric d p on the collection of binary phylogenetic trees each labelled by the same set of species. The metric is based on the so-called parsimony score, an important concept in phylogenetics that is commonly used to construct phylogenetic trees. Our main results include a characterization of the unit neighborhood of a tree in the d p metric, and an explicit formula for its diameter, that is, a formula for the maximum possible value of d p over all possible pairs of trees labelled by the same set of species. We also show that d p is closely related to the well-known tree bisection and reconnection (tbr) and subtree prune and regraft (spr) distances, a connection which will hopefully provide a useful new approach to understanding properties of these and related metrics.

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Section: Introductionmentioning

confidence: 99%

A parsimony-based metric for phylogenetic trees

Moulton

2015

Advances in Applied Mathematics

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“…Moreover, the usability and desirable properties of the MS distance have been confirmed by a recent work of Lin et al (2012). In particular, the authors showed that the MS metric performs significantly better than the well-known Robinson-Foulds distance (Robinson and Foulds, 1981) when applied to the clustering of phylogenetic trees.…”

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confidence: 79%

On a matching distance between rooted phylogenetic trees

Bogdanowicz¹,

Giaro²

2013

International Journal of Applied Mathematics and Computer Science

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The Robinson-Foulds (RF) distance is the most popular method of evaluating the dissimilarity between phylogenetic trees. In this paper, we define and explore in detail properties of the Matching Cluster (MC) distance, which can be regarded as a refinement of the RF metric for rooted trees. Similarly to RF, MC operates on clusters of compared trees, but the distance evaluation is more complex. Using the graph theoretic approach based on a minimum-weight perfect matching in bipartite graphs, the values of similarity between clusters are transformed to the final MC-score of the dissimilarity of trees. The analyzed properties give insight into the structure of the metric space generated by MC, its relations with the Matching Split (MS) distance of unrooted trees and asymptotic behavior of the expected distance between binary n-leaf trees selected uniformly in both MC and MS (Θ(n 3/2 )).

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“…Bootstrap support values can be determined for every branch that connects two inner nodes of the tree, that is, for each inner branch of the tree [5]. Support is a measure to give a score to each clade among all bootstrap replicates.…”

Section: Bootstrapping Phylogeneticmentioning

confidence: 99%