In this chapter, the Felsenstein’s pruning algorithm was presented and show to be used to calculate the likelihoods of Mk and extended-Mk models on phylogenetic trees. I have also described both ML and Bayesian frameworks that can be used to test hypotheses about character evolution. This chapter also includes a description of the “total garbage” test, which will tell you if your data has information about evolutionary rates of a given character.
- 8.1: The Evolution of Limbs and Limblessness
- Squamates had lost their limbs repeatedly over their evolutionary history. This is a pattern that has been known for decades, but analyses have been limited by the lack of a large, well-supported species-level phylogenetic tree of squamates. In the past few years have phylogenetic trees been produced at a scale broad enough to take a comprehensive look at this question. Such efforts to reconstruct this section of the tree of life provide exciting potential to revisit old questions with new data.
- 8.2: Fitting Mk models to Comparative Data
- The equations in Chapter 7 give us enough information to calculate the likelihood for comparative data on a tree. To understand how this is done, we can first consider the simplest case, where we know the beginning state of a character, the branch length, and the end state. We can then apply the method across an entire tree using a pruning algorithm, which will allow calculation of the likelihood of the data given the model and phylogenetic tree.
- 8.5: Exploring Mk - the "total garbage" test
- One problem that arises sometimes in maximum likelihood optimization happens when instead of a peak, the likelihood surface has a long flat “ridge” of equally likely parameter values. In the case of the Mk model, it is common to find that all values of q greater than a certain value have the same likelihood. This is because above a certain rate, evolution has been so rapid that all traces of the history of evolution of that character have been obliterated.
- 8.8: Appendix - Felsenstein's Pruning Algorithm
- Felsenstein’s pruning algorithm (1973) is an example of dynamic programming, a type of algorithm that has many applications in comparative biology. In dynamic programming, we break down a complex problem into a series of simpler steps that have a nested structure. This allows us to reuse computations in an efficient way and speeds up the time required to make calculations.