Usage ===== This section contains practical workflow tutorials based on the interactive user scripts provided with CellColoc. CellColoc is intended to be used through project-specific scripts that configure real datasets and then call the reusable package cell by cell in a VS Code interactive window or notebook-like environment. .. toctree:: :maxdepth: 2 usage_example_datasets usage_2d_dapi_stained_nuclei usage_results usage_3d_microglia usage_three_channel_analysis usage_three_channel_zprojection usage_2d_single_channel_dapi_nuclei Current usage topics -------------------- The documentation currently covers topics such as: - configuring channels and display names - loading microscopy datasets - whole-image analysis versus ROI-based analysis - ROI drawing and ROI reuse - choosing segmentation backends - using z-cropping and z-projection - refining `Cellpose `_ results post hoc - recomputing tables after manual mask edits - understanding exported result tables and masks - adapting the provided user scripts for new projects Recommended starting point -------------------------- If you are new to CellColoc, start with the 2D tutorial first. It introduces the interactive analysis model with the least amount of complexity and shows how a complete run is structured from configuration to export. The 3D tutorial then builds on the same ideas and adds z-aware features such as anisotropy handling, disk-backed loading, refinement-time z-cropping, and manual reanalysis of edited 3D label masks. The interactive scripts in the repository's ``user_scripts/`` directory show the same structure on real datasets and can be adapted directly for new projects. They show how to: - configure a project, - run the pipeline cell by cell, - inspect results in napari, - and export reproducible outputs.