Usageο
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.
- Example data set
- 2D data analysis tutorial
- Dataset used in this tutorial
- How to use this tutorial
- Imports
- Project settings
- Load the analysis channels
- Optional: Draw ROIs interactively in napari
- Optional: Save drawn ROIs or load an existing ROI mask
- Run the ROI-wise segmentation and colocalization analysis
- Visualize the result in napari
- Optional: Refine Cellpose thresholds and inspect the updated result
- Optional: Reanalyze manually edited label layers from napari
- Export results
- Adapting this tutorial to your own data
- Understanding exported results
- 3D data analysis tutorial
- Dataset used in this tutorial
- How to use this tutorial
- Imports
- Project settings
- Load the analysis channels
- Optional: Draw ROIs interactively in napari
- Optional: Save drawn ROIs or load an existing ROI mask
- Run the ROI-wise segmentation and colocalization analysis
- Visualize the result in napari
- Optionally set or update a global z-crop for subsequent refinement
- Optionally refine results and visualize the updated result
- Optionally reanalyze manually edited label layers from napari
- Export results
- Adapting this tutorial to your own data
- Three-channel analysis tutorial
- Dataset used in this tutorial
- How to use this tutorial
- Imports
- Project settings
- Load the analysis channels
- Optional ROI drawing and ROI reuse
- Run the ROI-wise three-channel segmentation and colocalization analysis
- Visualize the base result in napari
- Optional global z-crop for refinement
- Optionally refine all three channels and visualize the updated result
- Optional manual reanalysis after napari edits
- Visualize cells positive for channel 0 + channel 1
- Visualize cells positive for channel 0 + channel 2
- Visualize cells positive for channel 0 + channel 1 + channel 2
- Export results
- When to use this tutorial
- Three-channel analysis with z-projection tutorial
- Dataset used in this tutorial
- How to use this tutorial
- Imports
- Project settings
- Load the analysis channels
- Draw ROIs interactively in napari
- Save the drawn ROIs or load an existing ROI mask
- Run the ROI-wise three-channel segmentation and colocalization analysis
- Visualize the base result in napari
- Optionally refine the projected result and visualize the updated result
- Optionally reanalyze manually edited label layers from napari
- Visualize cells positive for channel 0 + channel 1
- Visualize cells positive for channel 0 + channel 2
- Visualize cells positive for channel 0 + channel 1 + channel 2
- Export results
- Single-channel analysis tutorial
- Dataset used in this tutorial
- How to use this tutorial
- Imports
- Project settings
- Load the analysis channel
- Optional: Draw ROIs interactively in napari
- Optional: Save drawn ROIs or load an existing ROI mask
- Run the ROI-wise single-channel segmentation and counting
- Visualize the result in napari
- Optional: Refine Cellpose thresholds and inspect the updated result
- Optional: Reanalyze manually edited label layers from napari
- Export results
- Result table: object_summary
- Result table: voxel_plausibility_check
- Result table: roi_overview
Current usage topicsο
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 pointο
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 repositoryβs 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.