CellColoc Documentation ======================== .. figure:: _static/CellColoc_2.png :alt: CellColoc overview :align: center :figwidth: 70% ­ .. image:: https://badgen.net/badge/icon/GitHub%20repository?icon=github&label :target: https://github.com/FabrizioMusacchio/cellcoloc/ :alt: GitHub Repository .. image:: https://img.shields.io/github/v/release/FabrizioMusacchio/cellcoloc :alt: GitHub Release .. image:: https://img.shields.io/pypi/v/cellcoloc.svg :target: https://pypi.org/project/cellcoloc/ :alt: PyPI version .. image:: https://img.shields.io/badge/License-GPL%20v3-green.svg :target: https://cellcoloc.readthedocs.io/en/latest/overview.html#license :alt: GPLv3 License .. image:: https://github.com/FabrizioMusacchio/cellcoloc/actions/workflows/cellcoloc_tests.yml/badge.svg :alt: Tests .. image:: https://codecov.io/gh/FabrizioMusacchio/cellcoloc/graph/badge.svg?token=OYTRL4WO0U :target: https://codecov.io/gh/FabrizioMusacchio/cellcoloc :alt: Codecov .. image:: https://img.shields.io/github/last-commit/FabrizioMusacchio/cellcoloc :target: https://github.com/FabrizioMusacchio/cellcoloc/commits/main/ :alt: GitHub last commit .. image:: https://img.shields.io/codecov/c/github/FabrizioMusacchio/cellcoloc?logo=codecov :target: https://codecov.io/gh/fabriziomusacchio/cellcoloc :alt: codecov .. image:: https://img.shields.io/github/issues/FabrizioMusacchio/cellcoloc :target: https://github.com/FabrizioMusacchio/cellcoloc/issues :alt: GitHub Issues Open .. image:: https://img.shields.io/github/issues-closed/FabrizioMusacchio/cellcoloc?color=53c92e :target: https://github.com/FabrizioMusacchio/cellcoloc/issues?q=is%3Aissue%20state%3Aclosed :alt: GitHub Issues Closed .. image:: https://img.shields.io/github/issues-pr/FabrizioMusacchio/cellcoloc :target: https://github.com/FabrizioMusacchio/cellcoloc/pulls :alt: GitHub Issues or Pull Requests .. image:: https://readthedocs.org/projects/cellcoloc/badge/?version=latest :target: https://cellcoloc.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status .. image:: https://img.shields.io/github/languages/code-size/fabriziomusacchio/cellcoloc :alt: GitHub code size in bytes .. image:: https://img.shields.io/pypi/dm/cellcoloc?logo=pypy&label=PiPY%20downloads&color=blue :target: https://pypistats.org/packages/cellcoloc :alt: PyPI Downloads .. image:: https://static.pepy.tech/personalized-badge/cellcoloc?period=total&units=INTERNATIONAL_SYSTEM&left_color=GRAY&right_color=BLUE&left_text=PiPY+total+downloads :target: https://pepy.tech/projects/cellcoloc :alt: PyPI Total Downloads .. image:: https://img.shields.io/badge/Example%20Datasets-10.5281%2Fzenodo.20788293-blue :target: https://doi.org/10.5281/zenodo.20788293 :alt: CellColoc example datasets on Zenodo .. image:: https://img.shields.io/badge/Zenodo%20Archive-10.5281%2Fzenodo.20787509-blue :target: https://doi.org/10.5281/zenodo.20787509 :alt: Zenodo Archive `CellColoc `_ is a Python package for interactive, segmentation-based colocalization analysis in microscopy images. It combines reusable core analysis logic with project-specific user scripts that can be executed step by step in VS Code or notebook-like environments. CellColoc supports both neural-network segmentation with Cellpose and classical threshold-based segmentation on a per-channel basis, including ROI- wise analysis, occupancy quantification, optional third-channel logic, fast post hoc refinement, and interactive napari inspection. .. toctree:: :maxdepth: 3 :caption: Contents overview installation usage api changelog contributing