Instructor: Will Freyman http://willfreyman.org
Coordinator: Carrie Tribble https://carrietribble.weebly.com/
Funded in part by UC Berkeley's Data Science program DS421
RevBayes represents a fundamental re-conception of phylogenetic modeling by adopting a graphical model framework in
which all probabilistic models are comprised of modular components that can be assembled in a myriad of ways.
The graphical models are specified using a highly flexible R-like language, Rev.
This workshop will focus on enabling participants to use Rev to specify custom arbitrarily complex phylogenetic models from simple component parts.
Instruction will combine short lectures introducing the theoretical and conceptual basis of each inference problem and hands-on computer tutorials
demonstrating how to explore these questions using RevBayes.
Previous experience with RevBayes is not necessary, though familiarity with phylogenetic inference using other software is expected.
This workshop is open to anyone interested, including students, staff, post-docs, and faculty from IB and beyond.
Please install the latest version (1.0.7) of RevBayes for this workshop. Some of the state-dependent speciation and extinction analyses will not work with earlier versions.
- February 26 (noon - 4 PM) [slides]
- What is a graphical model?
- Discriminative vs generative models
- Linear regression as a graphical model
- Ancestral state estimation as a graphical model
- Linking phylo comparative methods and tree inference through generative graphical models
- February 27 (noon - 4 PM)
- Correlated evolution of discrete characters [slides]
- model testing via Bayes factors or reversible-jump MCMC
- State-dependent speciation and extinction (BiSSE/MuSSE) [tutorial]
- Hidden Markov models and diversification (HiSSE)
- Cladogenetic SSE models (ClaSSE) and biogeography (DEC-SSE)
- Correlated evolution of discrete characters [slides]
The easiest way is to clone this entire repo:
git clone https://github.com/wf8/RevBayes_UC_Berkeley_2018_Workshop.git