E-Book, Englisch, 396 Seiten
Reihe: Chapman & Hall/CRC Mathematical and Computational Biology
Methods, Algorithms, and Applications
E-Book, Englisch, 396 Seiten
Reihe: Chapman & Hall/CRC Mathematical and Computational Biology
ISBN: 978-1-4665-0082-2
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
Encouraging interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the-art Bayesian statistics to the phylogenetics community. The book emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. It also discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. In addition, the book covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Bayesian phylogenetics: methods, computational algorithms, and applications
Introduction
Overview
Priors in Bayesian phylogenetics Ying Wang and Ziheng Yang
Introduction
Estimation of distance between two sequences
Priors on model parameters in Bayesian phylogenetics
Priors on the tree topology
Priors on times and rates for estimation of divergence times
Summary
IDR for marginal likelihood in Bayesian phylogenetics Serena Arima and Luca Tardella
Introduction
Substitution models: a brief overview
Bayesian model choice
Computational tools for Bayesian model evidence
Marginal likelihood for phylogenetic data
Discussion
Bayesian model selection in phylogenetics and genealogy-based population genetics Guy Baele and Philippe Lemey
Introduction
Prior and posterior-based estimators
Path sampling approaches
Simulation study: uncorrelated relaxed clocks
Practical example on demographic
Variable tree topology stepping-stone marginal likelihood estimation Mark T. Holder, Paul O. Lewis, David L. Swofford, and David Bryant
Introduction
The generalized stepping-stone (GSS) method
Reference distribution for tree topology
Example
Summary
Funding
Acknowledgements
Consistency of marginal likelihood estimation when topology varies Rui Wu, Ming-Hui Chen, Lynn Kuo, and Paul O. Lewis
Introduction
Notation and definitions
Empirical example
Discussion
Funding
Acknowledgements
Bayesian phylogeny analysis Sooyoung Cheon and Faming Liang
Introduction
Bayesian phylogeny inference
Monte Carlo methods for Bayesian phylogeny inference
Summary
Sequential Monte Carlo (SMC) for Bayesian phylogenetics Alexandre Bouchard-Côté
Using phylogenetic SMC samplers
How phylogenetic SMC works
Extensions and implementation issues
Discussion
Population model comparison using multi-locus datasets Michal Palczewski and Peter Beerli
Introduction
Bayesian inference of independent loci
Model comparison using our independent marginal likelihood sampler
Conclusion
Bayesian methods in the presence of recombination Mary K. Kuhner
Introduction to non-treelike phylogenies
Describing the ARG
Inference of the ARG
Mechanics of sampling ARGs
Hazards of Bayesian inference in the presence of recombination
Directions for future research
Open questions
Conclusions
Bayesian nonparametric phylodynamics Julia A. Palacios, Mandev S. Gill, Marc A. Suchard, and Vladimir N. Minin
Introduction
General model formulation
Priors on effective population size trajectory
Examples
Extensions and future directions
Sampling and summary statistics of endpoint-conditioned paths in DNA sequence evolution Asger Hobolth and Jeffrey L. Thorne
Introduction
Independent sites models and summary statistics
Dependent{site models and Markov chain Monte Carlo
Future directions for sequence paths with dependence models
Bayesian inference of species divergence times Tracy A. Heath and Brian R. Moore
Introduction
Priors on branch rates
Priors on node times
Priors for calibrating divergence times
Practical issues for estimating divergence times
Summary and prospectus
Index
