Bayesian Evolutionary Analysis with BEAST
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What are the models used in phylogenetic analysis and what exactly is involved in Bayesian evolutionary analysis using Markov chain Monte Carlo (MCMC) methods? How can you choose and apply these models, which parameterisations and priors make sense, and how can you diagnose Bayesian MCMC when things go wrong? These are just a few of the questions answered in this comprehensive overview of Bayesian approaches to phylogenetics. This practical guide: • Addresses the theoretical aspects of the field • Advises on how to prepare and perform phylogenetic analysis • Helps with interpreting analyses and visualisation of phylogenies • Describes the software architecture • Helps developing BEAST 2.2 extensions to allow these models to be extended further. With an accompanying website providing example files and tutorials (http://beast2.org/), this one-stop reference to applying the latest phylogenetic models in BEAST 2 will provide essential guidance for all users – from those using phylogenetic tools, to computational biologists and Bayesian statisticians.Read more
- Written by the lead authors of the BEAST software - it gives guidance on the theory and practice of Bayesian phylogenetic methods
- A foundation for making the leap from theory to practice with BEAST - the reader will learn how to develop their own evolutionary models and software extensions
- Examples files and downloadable resources for BEAST 2 - available at http://beast2.org/
Reviews & endorsements
"Want to construct a phylogeny, add in calibrated time points or work out the past history of an epidemic? The open source package BEAST has established itself as the industry standard for all this and more. This definitive book, explaining what is under the hood, how the user can customize extensions and most critically, a simple 'how to' users guide, is necessary reading for beginners and specialists alike."
Laurence D. Hurst, University of BathSee more reviews
"In concert with the dramatic improvements to DNA sequencing technology, Bayesian inference has revolutionized population genetics, phylogenetics, and divergence time estimation. A similar impact on epidemiology appears imminent via a suite of new Bayesian methods that incorporate host and pathogen DNA sequence data into established mathematical frameworks. This book is an accessible and thorough introduction to these Bayesian procedures. However, the book does far more than explain the theory. It also includes clear guides on how to use the BEAST 2 software for performing Bayesian analyses, and how to visualize the results. Because the software is designed to be extensible, the book instructs users to write their own code to supplement the diverse methods that are already implemented in BEAST 2. This book is timely and is written by two of the leaders of the field. I highly recommend it."
Jeff Thorne, North Carolina State University
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- Date Published: August 2015
- format: Adobe eBook Reader
- isbn: 9781316308486
- contains: 21 b/w illus. 70 colour illus. 9 tables
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
Part I. Theory:
2. Evolutionary trees
3. Substitution and site models
4. The molecular clock
5. Structured trees and phylogeography
Part II. Practice:
6. Bayesian evolutionary analysis by sampling trees
7. Setting up and running a phylogenetic analysis
8. Estimating species trees from multilocus data
9. Advanced analysis
10. Posterior analysis and post-processing
11. Exploring phylogenetic tree space
Part III. Programming:
12. Getting started with BEAST
13. BEAST XML
14. Coding and design patterns
15. Putting it all together
List of authors
List of subjects.
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