steinbock results of IMC example data

If you are working with these files, please cite them as follows:Windhager, J., Zanotelli, V.R.T., Schulz, D. et al. An end-to-end workflow for multiplexed image processing and analysis. Nat Protoc (2023). https://doi.org/10.1038/s41596-023-00881-0
This repository hosts the results of processing example imaging mass cytometry (IMC) data hosted at zenodo.org/record/5949116 using the steinbock framework available at github.com/BodenmillerGroup/steinbock. Please refer to steinbock.sh for how these data were generated from the raw data.
The following files are part of this repository:

panel.csv: contains channel information regarding the used antibodies in steinbock format
img.zip: contains hot pixel filtered multi-channel images derived from the IMC raw data. One file per acquisition is generated
images.csv: contains metadata per acquisition
pixel_classifier.ilp: ilastik pixel classifier (same as the  one in zenodo.org/record/6043544)
ilastik_crops.zip: image crops on which the ilastik classifier was trained (same as the ones in zenodo.org/record/6043544)
ilastik_img.zip: contains multi-channel images (one per acquisition) in .h5 format for ilastik pixel classification
ilastik_probabilities.zip: 3 channel images containing the pixel probabilities after pixel classification
masks_ilastik.zip: segmentation masks derived from the ilastik pixel probabilities using the cell_segmentation.cppipe pipeline
masks_deepcell.zip: segmentation masks derived by deepcell segmentation
intensities.zip: Contains one .csv file per acquisition. Each file contains single-cell measures of the mean pixel intensity per cell and channel based on the files in img.zip and masks_deepcell.zip.
regionprops.zip: Contains one .csv file per acquisition. Each file contains single-cell measures of the morphological features and location of cells based on masks_deepcell.zip.
neighbors.zip: Contains one .csv file per acquisition. Each file contains an edge list of cell IDs indicating cells in close proximity based on masks_deepcell.zip.
ome.zip: contains .ome.tiff files derived from img.zip; one file per acquisition
histocat.zip: contains single-channel .tiff files with segmentation masks derived from masks_deepcell.zip for upload to histoCAT (bodenmillergroup.github.io/histoCAT)
cells.csv: contains intensity and regionprop measurements of all cells
cells_csv.zip: contains intensity and regionprop measurements of all cells per acquisition
cells.fcs: contains intensity and regionprop measurements of all cells in fcs format
cells_fcs.zip: contains intensity and regionprop measurements of all cells per acquisition in fcs format
cells.h5ad: contains intensity, regionprop and neighbor measurements of all cells in anndata format
cells_h5ad: contains intensity regionprop and neighbor measurements of all cells per acquisition in anndata format
graphs.zip: contains spatial object graphs in .graphml format; one file per acquisition