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Welcome to the Bodenmiller Lab Github

This organization serves the purpose to collect analysis and software repositories associated to our research.

Multiplexed image analysis

General instructions on how to analyse imaging mass cytometry (IMC) data can be found in the IMC data analysis workflow. For general discussions and questions relating to IMC data analysis, please raise an issue here.

The following tools have been developed by the lab to perform multiplexed image analysis:

  • steinbock for containerized image processing and segmentation.
  • readimc for reading raw IMC data.
  • ImcSegmentationPipeline for interactive IMC data processing and segmentation.
  • napari-imc for interactive visualization of IMC raw data in napari.
  • cytomapper for multiplexed image visualization in R.
  • cytoviewer for interactive multiplexed image visualization in R.
  • imcRtools for single-cell and spatial analysis in R.
  • IMCDataAnalysis for a reproducible workflow on multiplexed image downstream analysis in R.
  • imcdatasets for a collection of publicly available IMC datasets in R.

Please open issues in the relevant repositories to file bug reports or feature requests.


  1. IMCDataAnalysis IMCDataAnalysis Public

    R based workflow for multiplexed imaging data

    HTML 26 10

  2. steinbock steinbock Public

    A toolkit for processing multiplexed tissue images

    Python 46 14

  3. ImcSegmentationPipeline ImcSegmentationPipeline Public template

    A pixel classification based multiplexed image segmentation pipeline

    Jupyter Notebook 80 34

  4. imcRtools imcRtools Public

    An R package for handling and analysing imaging mass cytometry data

    R 20 8

  5. cytomapper cytomapper Public

    R package for visualization of highly multiplexed imaging data

    R 32 8

  6. cytoviewer cytoviewer Public

    An interactive multi-channel image viewer for R

    R 5 1


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