title: Inferring ancestral sequences in taxon-rich phylogenies.
abstract: Statistical consistency in phylogenetics has traditionally referred to the accuracy of estimating phylogenetic parameters for a fixed number of species as we increase the number of characters. However, it is also useful to consider a dual type of statistical consistency where we increase the number of species, rather than characters. This raises some basic questions: what can we learn about the evolutionary process as we increase the number of species? In particular, does having more species allow us to infer the ancestral state of characters accurately? This question is particularly important when sequence evolution varies in a complex way from character to character, as methods applicable for i.i.d. models may no longer be valid. In this paper, we assemble a collection of results to analyse various approaches for inferring ancestral information with increasing accuracy as the number of taxa increases.
authors.affiliation: Méthodes et Algorithmes pour la Bioinformatique, LIRMM, CNRS - Université de Montpellier, 161 rue Ada, 34392 Montpellier, France. gascuel@lirmm.fr
authors.forename: Olivier
authors.initials: O
authors.lastname: Gascuel
authors.forename: Mike
authors.initials: M
authors.lastname: Steel
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D019143:Evolution, Molecular; D016013:Likelihood Functions; D008390:Markov Chains; D008957:Models, Genetic; D015233:Models, Statistical; D010802:Phylogeny; D011336:Probability