chronumental 0.0.53

Large timetrees

Chronumental

Chron​ologies from mon​umental phylogenetic trees

---

Chronumental is a tool for creating a "time-tree" (where distance on the tree represents time) from a phylogenetic divergence-tree (where distance on the tree reflects a number of genetic substitutions).

What sets Chronumental apart from most other tools is that it scales to extremely large trees, which can contain millions of nodes. Chronumental uses JAX to represent the task of computing a time tree in a differentiable graph for efficient calculation on a CPU or GPU.

📝 Read the preprint

📚 View the documentation

Installation

Method 1: Using pipx (recommended for basic use - installs in its own isolated environment)

pip install --local pipx
pipx install  chronumental

Method 2: In your python environment

pip install chronumental

Method 3: Bioconda

Chronumental is now available on bioconda

conda config --add channels bioconda
conda install chronumental

Usage

This demo uses trees and metadata collated by the UShER team.

wget https://hgwdev.gi.ucsc.edu/~angie/UShER_SARS-CoV-2/2021/10/06/public-2021-10-06.all.nwk.gz
wget https://hgwdev.gi.ucsc.edu/~angie/UShER_SARS-CoV-2/2021/10/06/public-2021-10-06.metadata.tsv.gz
chronumental --tree public-2021-10-06.all.nwk.gz --dates public-2021-10-06.metadata.tsv.gz --steps 100

📚 Please visit our documentation page to learn more about the parameters you can use to control Chronumental.

Integrations

Taxonium can automatically call Chronumental, and generate a combined visualisation that allows switching between distance and time phylogenies

Similar tools

TreeTime is a more advanced tool for inferring time trees. If you have a dataset of e.g. <10,000 rather than millions of nodes you are definitely best off trying it. The TreeTime readme also links to other similar tools.

Troubleshooting

• Chronumental uses the earliest date in your dataset as an anchor to calibrate everything else. If this earliest date is wrong due to a metadata error things won't work well.