Parsimony via Consensus

Bruen, Trevor C.; Bryant, David

doi:10.1080/10635150802040597

Cited by 17 publications

(19 citation statements)

References 24 publications

(24 reference statements)

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Section: Relation To Mrp and Its Statisticalmentioning

confidence: 94%

“…Proposition 1). However, the result from Bruen and Bryant (2007) does not guarantee that MRP produces an ML supertree even when β i = 1 for all i, as their approach constructs a median on a space of trees that are defined by splits rather than particular trees.We turn now to the question of the statistical consistency of MRP under the exponential model (1). It can be shown that MRP will be statistically consistent under the covering property (2) in some special cases.…”

mentioning

confidence: 94%

“…A most parsimonious tree (or trees) is then reconstructed from this data matrix. As shown recently by Bruen and Bryant (2007), there is a close analogy between MRP and consensus tree methods, which seek a median tree computed using the SPR (subtree prune and regraft) or TBR (tree bisection and reconnection) metric d (recall that a median tree for a profile P = (T 1 , . .…”

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confidence: 97%

“…One should not be surprised that the same optimality criterion can emerge from different conceptual bases. With standard phylogenetic reconstruction, choosing the tree that minimizes the number of evolutionary changes can be justified philosophically (with the principle of maximum parsimony) as a consensus method (Bruen and Bryant, 2007) or by using an explicitly statistical approach such as likelihood (Steel and Penny, 2000).We have not discussed algorithms to search for ML supertrees. As with classical phylogenetic likelihood methods, maximum likelihood supertrees will be obtained using a variety of approaches, including heuristic methods, genetic algorithms, simulated annealing, and so on.…”

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confidence: 99%

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Maximum Likelihood Supertrees

2008

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We analyze a maximum likelihood approach for combining phylogenetic trees into a larger "supertree." This is based on a simple exponential model of phylogenetic error, which ensures that ML supertrees have a simple combinatorial description (as a median tree, minimizing a weighted sum of distances to the input trees). We show that this approach to ML supertree reconstruction is statistically consistent (it converges on the true species supertree as more input trees are combined), in contrast to the widely used MRP method, which we show can be statistically inconsistent under the exponential error model. We also show that this statistical consistency extends to an ML approach for constructing species supertrees from gene trees. In this setting, incomplete lineage sorting (due to coalescence rates of homologous genes being lower than speciation rates) has been shown to lead to gene trees that are frequently different from species trees, and this can confound efforts to reconstruct the species phylogeny correctly.

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Section: Relation To Mrp and Its Statisticalmentioning

confidence: 94%

mentioning

confidence: 94%

mentioning

confidence: 97%

mentioning

confidence: 99%

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Maximum Likelihood Supertrees

2008

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“…To establish (6), consider first the extension χ of χ defined by χ(v) = 1 for every interior vertex v of T . Then we have ∆(χ) = n − k if n = k 2 and ∆(χ) = n − k − 1 otherwise.…”

Section: The Diameter Of D Pmentioning

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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An Introduction to Supertree Construction (and Partitioned Phylogenetic Analyses) with a View Toward the Distinction Between Gene Trees and Species Trees

Bininda‐Emonds

2014

Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology

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Parsimony via Consensus

Cited by 17 publications

References 24 publications

Maximum Likelihood Supertrees

Maximum Likelihood Supertrees

A parsimony-based metric for phylogenetic trees

An Introduction to Supertree Construction (and Partitioned Phylogenetic Analyses) with a View Toward the Distinction Between Gene Trees and Species Trees

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