Dodonaphy

Hyperbolic embeddings for approximating phylogenetic posteriors.

This code is under active research & development and not intended for production use for phylogenetic inference.

Installing with Conda and Pip

First install the Python version of hydra+ from https://github.com/mattapow/hydraPlus.

Use python version 3.7 in order to use the bito package (for more models and to make use of BEAGLE).

conda create --name dodonaphy python=3.9
conda activate dodonaphy

Pip needs numpy and cython for the setup:

pip install cython
pip install numpy

Then install the Dodonaphy locally package using pip:

pip install -e .

Running tests

(Optional, requires pytest) Once the package is installed, tests are run using pytest:

pytest -o "testpaths=test"

Model

The basic idea is to embed genetic data as points in Hyperbolic space and connect them to form a tree. Then perform Bayesian inference (MCMC or Variational Inference) in the embedding space. Gradient ascent is performed using pytorch.

Basic usage

Run Dodonaphy using

dodo [OPTIONS]

As an example, data in the example directory is provided. Perform MCMC with a gamma dirichlet prior on the example data as follows.

dodo --infer mcmc --path_root example --prior gammadir --epochs 10000

This starts from the neighbour joining tree. To start from a better tree, use:

dodo --infer mcmc --path_root example --prior gammadir --epochs 10000 --start start.nex --suffix good_start

This creates a directory contained in mcmc/up_nj/d3_k0, signifying the embedding method "up", the tree connection method "nj" Neighbour Joining, three dimensions and a log negative curvature of 0, i.e. a curvature of -1. This directory has:

• samples.t containing sampled trees in the posterior
• locations.csv containing the tip embedding locations
• mcmc.log with information about the MCMC invoked.

Help

At the command line, type dodo --help to see the options.