Combine multiple imaging modalities of the same tissue section — DESI mass spectrometry imaging, microscopy images (e.g. H&E), SCRINSHOT data and ImageJ ROI annotations — into a single SpatialData object, applying affine transformations to align the modalities in a shared coordinate system. The resulting object is then exported as a TissUUmaps project for interactive visualization.
Inputs are described in a YAML configuration file (see notebooks/params_examples/), and multiple samples can be merged into a single SpatialData object for joint visualization.
- Clone this repository locally.
- Install pixi.
Note: The pixi environment is currently defined for Windows (win-64) only. Reading whole-slide images additionally requires OpenSlide installed in
C:\openslide.
- Create a YAML configuration file describing your input data (images, ROIs, transformations, DESI data). Examples are provided in notebooks/params_examples/.
- In a terminal or powershell, run:
pixi run create_spatialdata
- In a terminal or powershell, run:
A Jupyter-lab tab should open in your browser. In Jupyter-lab, navigate to the notebook notebooks/create_spatialdata.ipynb. Change input and output folders depending on the data location on your disk.
pixi run jupyter lab - Run the notebook. Use notebooks/merge_sdata.ipynb to merge multiple SpatialData objects into one.
- Test TissUUmaps output in TissUUmaps.
SciLifeLab BioImage Informatics Facility (BIIF)
Developed by Christophe Avenel