The APx Fractal Task Collection is mainainted by Apricot Therapeutics AG, Switzerland. This is a collection of tasks intended to be used in combination with the Fractal Analytics Platform maintained by the BioVisionCenter Zurich (co-founded by the Friedrich Miescher Institute and the University of Zurich). The tasks in this collection are focused on extending Fractal's capabilities of processing 2D image data, with a special focus on multiplexed 2D image data. Most tasks work with 3D image data, but they have not specifically been developed for this scenario.
You can install the package locally with:
pip install git+https://github.com/Apricot-Therapeutics/APx_fractal_task_collection.gitFor instructions on how to run tasks, please refer to the official Fractal Tasks Core Documentation
Please note that all tasks pass basic tests based on 2D and 3D OME-ZARR files. However, in the 3D case, the resulting output has not been extensively checked and might not make sense (as most tasks have been developed for the 2D use-case). If you are using the tasks for 3D data and encounter any weird behaviour, please open an issue.
| Task | Description | 2D Tests Passing | 2D Output validated | 3D Tests Passing | 3D Output validated |
|---|---|---|---|---|---|
| Create OME-Zarr Multiplex IC6000 | Generates a OME-Zarr file based on the output of a IN Cell Analyzer 6000 (GE Healthcare). | ☑️ | ☑️ | ☑️ | ✖️ |
| IC6000 to OME-Zarr | Converts output images from IC6000 microscopy to OME-Zarr. Use after "Create OME-Zarr Multiplex IC6000". | ☑️ | ☑️ | ☑️ | ✖️ |
| Calculate Illumination Profiles | Calculates illumination correction model based on BaSiCPy for each available channel. | ☑️ | ☑️ | ☑️ | ✖️ |
| Apply BaSiCPy Illumination Model | Applies BaSiCPy illumination models to a OME-Zarr file. Use after "Calculate Illumination Profiles" | ☑️ | ☑️ | ☑️ | ✖️ |
| Chromatic Shift Correction | Corrects chromatic shift in OME-Zarr file per wavelength id. Requires reference images (for example fluorescent beads) | ☑️ | ☑️ | ☑️ | ✖️ |
| Stitch FOVs with Overlap | Stitches FOVs that were imaged with overlap, using ASHLAR. | ☑️ | ☑️ | ☑️ | ✖️ |
| Calculate Registration (image-based) [chi-squared shift] | Calculates shift between acquisitions based on chi-squared shift algorithm from the python package image registration | ☑️ | ☑️ | ☑️ | ✖️ |
| Segment Secondary Object | Segments secondary objects in images. Requires a label image that provides seeds and an intensity image. | ☑️ | ☑️ | ☑️ | ✖️ |
| Clip Label Image | Clips a label image with a secondary label image. For example, this can be used to clip cell segmentations with nuclear segmentations to receive the cytoplasm. | ☑️ | ☑️ | ☑️ | ✖️ |
| Convert Channel to Label | Utility task to convert a channel from a OME-Zarr file to a label image. Can be used to import an external label image into Fractal without creating a new task. | ☑️ | ☑️ | ☑️ | ✖️ |
| Filter Label by Size | Filters a label image by size and removes objects larger/smaller than a given threshold. | ☑️ | ☑️ | ☑️ | ✖️ |
| Measure Features | Measures features for a given label image. Currently, four feature sets are available: intensity featues, morphology features, population context features and texture features (Haralick and Law's Texture Energy). | ☑️ | ☑️ | ☑️ | ✖️ |
| Label Assignment by Overlap | Assigns child labels to parent labels by their overlap. Relationship is saved in the observations of the feature table. | ☑️ | ☑️ | ☑️ | ✖️ |
| Aggregate Tables to Well Level | Aggregates/Concatenates feature tables from all acquisitions. Can be saved either on the well level or in the first aqcuisition. | ☑️ | ☑️ | ☑️ | ✖️ |
| Compress Zarr for Visualization | (EXPERIMENTAL) Strong compression of OME-Zarr file for easier visualization in napari. | ☑️ | ☑️ | ☑️ | ✖️ |
| Multiplexed Pixel Clustering | Applies multiplexed pixel clustering to selected images. | ☑️ | ☑️ | ☑️ | ✖️ |