Analysis of Phylogenetics and Evolution with R

The increasing availability of molecular and genetic databases coupled with the growing power of computers gives biologists opportunities to address new issues, such as the patterns of molecular evolution, and re-assess old ones, such as the role of adaptation in species diversification.

This book integrates a wide variety of data analysis methods into a single and flexible interface: the R language. This open source language is available for a wide range of computer systems and has been adopted as a computational environment by many authors of statistical software. Adopting R as a main tool for phylogenetic analyses will ease the workflow in biologists' data analyses, ensure greater scientific repeatability, and enhance the exchange of ideas and methodological developments.

Graduate students and researchers in evolutionary biology can use this book as a reference for data analyses, whereas researchers in bioinformatics interested in evolutionary analyses will learn how to implement these methods in R. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered: manipulation of phylogenetic data, phylogeny estimation, tree drawing, phylogenetic comparative methods, and estimation of ancestral characters. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters.

Emmanuel Paradis is an evolutionary biologist at the Centre National de la Recherche Scientifique (CNRS) and the Institut de Recherche pour le Développement (IRD) in Montpellier. He received his Doctorate Diploma in population biology and ecology in 1993 at theUniversity of Montpellier II. He has conducted empirical and theoretical research on birds, mammals, and fish. He worked at the British Trust for Ornithology for three years and at the Institut des Sciences de l'Évolution in Montpellier for seven years where he developed most of the ideas presented in this book. He is the main author and maintainer of the R package APE (Analysis of Phylogenetics and Evolution).

Résumé
As a result, the inference of phylogenies often seems divorced from any connection to other methods of analysis of scienti?c data. Felsenstein Once calculation became easy, the statistician's energies could be - voted to understanding his or her dataset. Venables & Ripley The study of the evolution of life on Earth stands as one of the most complex ?elds in science. It involves observations from very di?erent sources, and has implications far beyond the domain of basic science. It is concerned with processes occurring on very long time spans, and we now know that it is also important for our daily lives as shown by the rapid evolution of many pathogens. As a ?eld ecologist, for a long time I was remotely interested in phylo- netics and other approaches to evolution. Most of the work I accomplished during my doctoral studies involved ?eld studies of small mammals and es- mation of demographic parameters. Things changed in 1996 when my interest was attracted by the question of the e?ect of demographic parameters on bird diversi?cation. This was a new issue for me, so I searched for relevant data analysis methods, but I failed to ?nd exactly what I needed. I started to conduct my own research on this problem to propose some, at least partial, solutions. This work made me realize that this kind of research critically - pends on the available software, and it was clear to me that what was o?ered to phylogeneticists at this time was inappropriate.

Contenu
First Steps in R for Phylogeneticists.- Phylogenetic Data in R.- Plotting Phylogenies.- Phylogeny Estimation.- Analysis of Macroevolution with Phylogenies.- Developing and Implementing Phylogenetic Methods in R.