Class materials

Several of the modules below use R and packages ape, diversitree, phytools, mvtnorm, geiger.

Bring your own data (tree files, perhaps trait files) if you like. We’ll have some time for you to try fitting models while asking instructors for help. But recall that the main emphasis of this workshop is learning about how models think, rather than specific software packages.

Probability basics

MTH slides (borrowing heavily from Paul Lewis) are:

• https://mtholder.github.io/reveal/midwest-phylo.html#/ and
• https://mtholder.github.io/reveal/midwest-phylo-likelihood.html#/

The source for the slides is are in https://github.com/mtholder/reveal

The JavaScript apps used by MTH for teaching are at http://phylo.bio.ku.edu/mephytis/ and their source is https://github.com/mtholder/mephytis

Likelihood and Evidence

RZF Heterospecific alarm calls example

• R code
• Data

Bayesian intro

TAH slides (borrowing heavily from Paul Lewis) are:

• Bayesian introduction

Discrete traits

MTH ran through John Huelsenbeck’s simulation of a character with dice see instructions. Model slides were slides 2-15 of the second part of Paul Lewis’ Woods Hole likelihood lecture.

RZF Introduction to continuous-time Markov chain models

• Likelihood for discrete trait models

HLB Coding discrete trait models in diversitree

• Tutorial on discrete trait analysis

Bayesian tree inference, divergence times, joint inference

TAH slides:

• Probabilistic graphical models
• Divergence-time estimation and joint inference

Continuous traits

• Slides
• Handout with full explanations and code
• Folder of papers

Birth-death

Basic overview:

• Key questions
• Basic concepts & terminology
• Pure-birth (Yule) process
• Birth-death process
• Concepts in tree shape (LTT, balance, etc)
• Helpful guidelines for macroevolutionary modeling
• Building intuition for macroevolutionary outcomes

Class exercise stuff:

• Pure-birth model: analytical derivation
• get the data
• Exercise template
• helper functions here

Full code for all class exercises:

• Basic birth-death here
• Among-lineage variation here
• Temporal variation here

Birth-death-traits

General plan and a few references:

• Macroevolutionary questions
• Sister clade test (review and new test: Paradis 2012)
• Confounding diversification and trait evolution (Maddison 2006)
• Integrative model (Maddison et al. 2007)
• Model comparison issues (Maddison & FitzJohn 2015, Rabosky & Goldberg 2015)
• New approaches (Beaulieu & O’Meara 2016)

Code:

• Live-coding is encouraged, but here is the code if you prefer
• Do download this file of helper functions for use in class
• For the empirical tree example, use this cetacean tree or your own

Phylo networks

slides

tutorial:

• install julia & packages: instructions
• get the data
• estimate a network
• julia code

Open science / reproducibility

Motivation for and overview of:

• version control: git (slides), GitHub
• reproducible analyses with focus on communication: Rmarkdown reports, markdown format
• text editor: e.g. Atom or VS Code
• basic shell tools are powerful

To learn more: there are lots of resources online, e.g. courses for on computational skills for biology graduate students:

• at Iowa State U
• at UW-Madison

Additional Tutorials and Resources

• The RevBayes Tutorials Page: https://revbayes.github.io/tutorials/
• Tutorials for BEAST2 from Taming the BEAST: https://taming-the-beast.org/tutorials/
• LaTeX tutorial