@article {921311,
	title = {Coalescent methods for estimating phylogenetic trees},
	journal = {Mol Phylogenet Evol},
	volume = {53},
	number = {1},
	year = {2009},
	note = {<p>Liu, LiangYu, LiliKubatko, LauraPearl, Dennis KEdwards, Scott VResearch Support, U.S. Gov{\textquoteright}t, Non-P.H.S.ReviewUnited StatesMolecular phylogenetics and evolutionMol Phylogenet Evol. 2009 Oct;53(1):320-8. Epub 2009 Jun 6.</p>},
	month = {Oct},
	pages = {320-8},
	abstract = {<p>We review recent models to estimate phylogenetic trees under the multispecies coalescent. Although the distinction between gene trees and species trees has come to the fore of phylogenetics, only recently have methods been developed that explicitly estimate species trees. Of the several factors that can cause gene tree heterogeneity and discordance with the species tree, deep coalescence due to random genetic drift in branches of the species tree has been modeled most thoroughly. Bayesian approaches to estimating species trees utilizes two likelihood functions, one of which has been widely used in traditional phylogenetics and involves the model of nucleotide substitution, and the second of which is less familiar to phylogeneticists and involves the probability distribution of gene trees given a species tree. Other recent parametric and nonparametric methods for estimating species trees involve parsimony criteria, summary statistics, supertree and consensus methods. Species tree approaches are an appropriate goal for systematics, appear to work well in some cases where concatenation can be misleading, and suggest that sampling many independent loci will be paramount. Such methods can also be challenging to implement because of the complexity of the models and computational time. In addition, further elaboration of the simplest of coalescent models will be required to incorporate commonly known issues such as deviation from the molecular clock, gene flow and other genetic forces.</p>},
	keywords = {*Models, Genetic, *Phylogeny, Bayes Theorem, Evolution, Molecular, Genetic Speciation, Likelihood Functions, Sequence Analysis, DNA/*methods, Statistics, Nonparametric},
	isbn = {1095-9513 (Electronic)1055-7903 (Linking)},
	author = {Liu, L. and Yu, L. and Kubatko, L. and Pearl, D. K. and Edwards, S. V.}
}
