LDA on Trees

The goal of this study is to look at some of the potential uses of LDA in phylogenetic inference. The major components of this project are:

1. Create a transition count matrix from a tree
2. Run LDA on substition count matrices as a controlled example
3. Run LDA on more interesting examples

More about Ipython Notebooks and the methods herein

This notebook uses the IPython Notebook to communicate ideas, models etc. The focus is on Bayesian methods for phylogenetic inference. In general we use PyMC as a sandbox, GitHub as a repository and Python to glue it together.

A major resource (and highly recommended if you do not know it already) is Cameron Davidson-Pilon's book Bayesian Methods for Hackers. The full Github repository is available at github/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers. The other chapters can be found on the project's homepage. Another resource is a course (see below) by Chris Fonnesbeck one of the main PyMC developers.

• IPython notebook introduction
• Markdown syntax
• Advanced Statistical Computing - C Fonnesbeck

To get started simply download move into the source directory and type

~$ ipython notebook