phytclust 0.1.1

PhytClust takes a phylogenetic tree as input and outputs monophyletic leaf clusters that best fit the tree structure.

PhytClust

Monophyletic, dynamic-programming clustering of phylogenetic trees.

PhytClust finds clusterings of the leaves of a rooted tree such that every cluster is a monophyletic clade. It supports:

• Exact k-way clustering (run(k=...))
• Global peak search in k using a Calinski–Harabasz + Elbow 1 Index for validating cluster quality
• Multi-resolution clustering: one representative k per log-spaced resolution bin
• Polytomies, minimum cluster size constraints, support-aware branch lengths, outlier penalties and more!

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Installation

1. Recommended: clean conda environment and install with PyPI

conda create -n phyt_env python=3.10
conda activate phyt_env
pip install phytclust

2. Install from source

git clone https://bitbucket.org/schwarzlab/phytclust.git
cd phytclust
pip install -e .[dev]

Command-line usage

Exact k clusters

Compute an exact k-way clustering, plot it, and save PNG + CSV under ./results:

phytclust tree.nwk --k 5 --save-fig --out-dir results

Global clustering solution

Search for the top 3 Calinski–Harabasz + Elbow index peaks up to k = 200, save everything in ./out:

phytclust tree.nwk --top-n 3 \
  --max-k 200 \
  --save-fig \
  --out-dir out

Multi-resolution clustering

Pick one representative peak per 4 log-spaced bins of k, don’t show plots interactively, save all k-specific CSVs and plots:

phytclust tree.nwk --bins 4 \
  --no-plot \
  --save-all-k \
  --save-fig \
  --out-dir out

(See phytclust --help for the complete CLI.)

Please cite

Please cite this repository if you use the algorithm in your work:

K. Ganesan, E. Billard, T.L. Kaufmann, C. B Strange, M. C. Cwikla, A. Altenhoff, C. Dessimoz, R.F. Schwarz, PhytClust, (2025), Bitbucket repository, https://bitbucket.org/schwarzlab/phytclust/