IMC Segmentation Pipeline results of example IMC data

This repository hosts the results of processing example imaging mass cytometry (IMC) data hosted at 10.5281/zenodo.5949116 using the IMC Segmentation Pipeline available at https://github.com/BodenmillerGroup/ImcSegmentationPipeline (DOI: 10.5281/zenodo.6402666). Please refer to https://github.com/BodenmillerGroup/steinbock as alternative processing framework and 10.5281/zenodo.6043600 for the data generated by steinbock.

The following files are part of the analysis.zip folder when running the IMC Segmentation Pipeline:

• cpinp: contains input files for the segmentation pipeline
• cpout: contains all final output files of the pipeline: cell.csv containing the single-cell features; Experiment.csv containing CellProfiler metadata; Image.csv containing acquisition metadata; Object relationships.csv containing an edge list indicating interacting cells; panel.csv containing channel information; var_cell.csv containing cell feature information; var_Image.csv containing acquisition feature information; images containing the hot pixel filtered multi-channel images and the channel order; masks containing the segmentation masks; probabilities containing the pixel probabilities.
• histocat: contains single channel .tiff files per acquisition for upload to histoCAT (https://bodenmillergroup.github.io/histoCAT/)
• crops: contains upscaled image crops in .h5 format for ilastik (https://www.ilastik.org/) training 
• ometiff: contains .ome.tiff files per acquisition, .png files per panorama and additional metadata files per slide
• ilastik: multi channel images for ilastik pixel classification (_ilastik.full) and their channel order (_ilastik.csv); upscaled multi channel images for ilastik pixel prediction (_ilastik_s2.h5); upscaled 3 channel images containing ilastik pixel probabilities (_ilastik_s2_Probabilities.tiff).

The remaining files are part of the root directory:

• docs.zip: Documentation of the pipeline in markdown format
• IMCWorkflow.ilp: Ilastik pixel classifier pre-trained on the example data
• resources.zip: The CellProfiler pipelines and CellProfiler plugins used for the analysis
• sample_metadata.xlsx: Metadata per sample including the cancer type
• scripts.zip: Python notebooks used for pre-processing and downloading the example data
• src.zip: Scripts for the imcsegpipe python package