title: Inferring Trees.
abstract: Molecular evolution can reveal the relationship between sets of homologous sequences and the patterns of change that occur during their evolution. An important aspect of these studies is the inference of a phylogenetic tree, which explicitly describes evolutionary relationships between homologous sequences. This chapter provides an introduction to evolutionary trees and how to infer them from sequence data using some commonly used inferential methodology. It focuses on statistical methods for inferring trees and how to assess the confidence one should have in any resulting tree, with a particular emphasis on the underlying assumptions of the methods and how they might affect the tree estimate. There is also some discussion of the underlying algorithms used to perform tree search and recommendations regarding the performance of different algorithms. Finally, there are a few practical guidelines, including how to combine multiple software packages to improve inference, and a comparison between Bayesian and Maximum likelihood phylogenetics.
authors.affiliation: Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden. Simon.Whelan@ebc.uu.se.
authors.forename: Simon
authors.initials: S
authors.lastname: Whelan
authors.affiliation: Department of Organism Biology, Uppsala University, Uppsala, Sweden.
authors.forename: David A
authors.initials: DA
authors.lastname: Morrison
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods*; D019143:Evolution, Molecular; D016013:Likelihood Functions; D008957:Models, Genetic; D010802:Phylogeny
keywords: Distance methods; Evolutionary trees; Maximum likelihood; Parsimony; Phylogenetic inference; Review