campmc 0.1.1

Third-party portable Python package for CAMP metacell partitioning (not the official paper repo)

CAMP (Coreset Accelerated Metacell Partitioning)

Third-party, installable Python reimplementation of the CAMP metacell methods for use with AnnData and Scanpy.

About this project

This repository is not maintained by the authors of the CAMP paper. It is an independent packaging effort that ports the research code from the upstream CAMP repository into a reusable library (import campmc as cp, PyPI name campmc).

Goals of this project:

• Make CAMP1–4 and related helpers portable (no hardcoded cluster paths, scanpy-style API).
• Provide tests, documentation, and a normal Python package layout.

For the official reference implementation, paper benchmarks, and experiment scripts, use the upstream CAMP repository. Behavior here should match the published algorithms in spirit, but this package is maintained separately.

If you use the CAMP method, please cite the bioRxiv preprint (Li, Ko & Canzar, 2025; doi:10.64898/2025.12.11.693725) — see Citation below.

Install

pip install campmc

Or with uv: uv add campmc.

For development from a clone:

git clone https://github.com/nictru/campmc.git
cd campmc
uv sync --group dev

Usage (scanpy-style)

import campmc as cp
import scanpy as sc

adata = sc.datasets.pbmc68k_reduced()
cp.tl.partition(adata, method="camp3", gamma=25, random_state=0)
cp.metrics.quality(adata, partition_key="camp", label_key="louvain")

Documentation

Published docs: campmc.readthedocs.io

To build HTML locally (Sphinx, MyST, scanpydoc theme, same style as Scanpy):

uv sync --group doc
uv run sphinx-build -M html docs docs/_build

Citation

If you use the CAMP method, please cite the preprint:

Li, D., Ko, Y. K., & Canzar, S. (2025). CAMP: Coreset Accelerated Metacell Partitioning enables scalable analysis of single-cell data. bioRxiv. https://doi.org/10.64898/2025.12.11.693725

Preprint: bioRxiv

@article{li2025camp,
  title   = {CAMP: Coreset Accelerated Metacell Partitioning enables scalable analysis of single-cell data},
  author  = {Li, Danrong and Ko, Young Kun and Canzar, Stefan},
  journal = {bioRxiv},
  year    = {2025},
  doi     = {10.64898/2025.12.11.693725},
  url     = {https://www.biorxiv.org/content/10.64898/2025.12.11.693725v1}
}

This campmc package is a third-party implementation; citing the preprint refers to the CAMP method, not this repository.

Tests

uv run pytest -q

License

MIT — see LICENSE. Algorithm code is adapted from the upstream CAMP repository (MIT, © danrongLi). This campmc package is a separate third-party distribution; it is not affiliated with or endorsed by the original CAMP authors unless they state otherwise.