Maximum Likelihood Supertrees

dc.creatorSteel, Mike
dc.creatorRodrigo, Allen
dc.date2007-08-16
dc.date.accessioned2026-07-07T08:23:51Z
dc.date.available2026-07-07T08:23:51Z
dc.descriptionWe analyse 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, minimising 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.
dc.description13 pages, 0 figures
dc.identifierhttps://arxiv.org/abs/0708.2124
dc.identifierhttp://arxiv.org/abs/0708.2124
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/136148
dc.subjectPopulations and Evolution
dc.subjectQuantitative Methods
dc.titleMaximum Likelihood Supertrees
dc.typetext

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