Metadata-Version: 2.4
Name: Compocyte
Version: 0.0.2b0
Summary: Compocyte automates cell type annotation for scRNAseq data using a composite of hierarchically arranged classifiers.
Project-URL: Homepage, https://github.com/WALL-E-Lab/Compocyte
Project-URL: Bug Tracker, https://github.com/WALL-E-Lab/Compocyte/issues
Author-email: Thomas Walle <t.walle@dkfz-heidelberg.de>, Christopher Beltz <christopher.beltz@dkfz-heidelberg.de>
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.14
Requires-Dist: anndata==0.12.11
Requires-Dist: balanced-loss==0.1.1
Requires-Dist: catboost==1.2.10
Requires-Dist: cytopus==1.3.4
Requires-Dist: dask==2026.3.0
Requires-Dist: leidenalg==0.11.0
Requires-Dist: pooch==1.9.0
Requires-Dist: pygraphviz==1.14
Requires-Dist: pytest==9.0.3
Requires-Dist: scanpy==1.12.1
Requires-Dist: scikit-learn==1.8.0
Requires-Dist: seacells==0.3.3
Requires-Dist: torch==2.11.0
Provides-Extra: dev
Provides-Extra: docs
Requires-Dist: furo>=2024.01.29; extra == 'docs'
Requires-Dist: ipython>=8.0.0; extra == 'docs'
Requires-Dist: myst-parser>=2.0.0; extra == 'docs'
Requires-Dist: nbsphinx>=0.9.0; extra == 'docs'
Requires-Dist: sphinx-design>=0.5.0; extra == 'docs'
Requires-Dist: sphinx>=7.0; extra == 'docs'
Description-Content-Type: text/markdown

# Compocyte

<strong>Compocyte</strong> is a composite classifier for modular hierarchical cell type annotation of single cell data. Using Compocyte you can build different hierarchical classifier architectures following a local classifier per parent node approach. Local classifiers are built around pytorch, sklearn or CatBoost. Local classifiers can be individually modified to account for alterations in classification taxonomies or selectively improve specific annotations in human-in-the-loop approaches. While compocyte has been primarily developed for single cell RNA sequencing data it can also be used with other single cell data compatible with the AnnData and scanpy packages.

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# Getting started

For a quick dive into using Compocyte to label single-cell data, refer to our [Getting started](https://compocyte.readthedocs.io/en/latest/tutorials/getting_started.html) on readthedocs. There, you can also find tutorials to help you make full use of Compocyte's features.

# Citation

When using our pretrained classification models, please cite the Zenodo publications above.

When using Compocyte, please cite our publication (DOI will be provided shortly).
