P4¶
P4 is a Python package for maximum likelihood and Bayesian analysis of molecular sequences. Its specialty is that it can use heterogeneous models, where the characteristics of the model can differ over the data or over the tree.
P4 is also a phylogenetic toolkit. The interface for p4 is the Python programming language, so p4 comes with all the abilities of a high-level object oriented programming language. This is a Good Thing, but it means that you need to know some Python in order to use it. It can be useful for things like programmatic manipulation of trees or data.
It is hosted at https://github.com/pgfoster/p4-phylogenetics
- Introduction
- News
- Installation
- Tutorials and Examples
- Introduction
- Using p4
- Customizing
- Alignments and data
- Trees
- Models and likelihood
- Simulating data
- Simulations with reference data
- Bayesian analysis with MCMC
- Compositional homogeneity tests
- Model fit tests
- Drawing trees
- To collapse nodes in a tree
- To combine tree supports from two analyses onto one tree
- Making a tree from compositions
- Doing MRP, Matrix representation / parsimony
- Kosiol’s AIS, almost invariant sets
- Assessing partition composition differences
- Testing whether two unrelated sequences have different compositions
- Testing whether two related sequences have different compositions
- Testing whether two related partitions have different compositions
- Comparing constant with variable sites
- Comparing autapomorphic sites with other variable sites
- An example using the Cox et al 2008 data
- Ancestral character state reconstruction
- Scripts for common tasks
- Make a consensus tree, with variations
- Make a consensus tree, uncomplicated
- Calculate a likelihood
- Calculate likelihood with more than one data partition
- Do an MCMC
- Do an MCMC with more than one data partition
- Read checkPoints from an MCMC
- Restart an MCMC
- Simulate data
- Simulate data with more than one data partition
- Simulate very hetero data
- Classes and Modules