bioRxivBioinformaticsPreprint
CellMAPS: A no-code model-based customisable multiplex image analysis workflow
Éanna FennelliD, Colm BrandoniD, Steve BoßelmanniD, Stephen RyaniD, Amandeep SinghiD, Aoife S. HennessyiD, Aisling M. RossiD, Ciara I. LeahyiD, Matthew PughiD, Nadezhda NikulinaiD, Oliver BraubachiD, Gerald NiedobitekiD, Graham S. TayloriD, Tiziana MargariaiD, Paul Gerard MurrayiD
Abstract
Although multiplex imaging allows simultaneous mapping of complex tissue architectures and cellular phenotypes, the dearth of user-friendly robust image analysis workflows remains a significant limitation to its widespread use, restricting multiplex imaging to laboratories with image analysis expertise. Here, we introduce a no-code model-based customisable suite, CellMAPS, which allows both image processing and spatial analyses by non-specialists. We also developed new tools for tissue de-arraying, image normalisation and cell segmentation to increase usability and reduce analysis subjectivity. We have also introduce new spatial analysis tools for the partition of tissue architectures and cellular microenvironments. We demonstrate the capabilities of CellMAPS in various diseases captured using different multiplex imaging platforms. Overall, CellMAPS provides a platform for inexperienced laboratories to implement multiplex imaging and complex spatial analyses, which ultimately should lead to the broader adoption of these technologies in the biomedical field.
- Citations
- 3
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Streamlining Multiplexed Tissue Image Analysis with PIP{Sigma}X: An Integrated Automated Pipeline for Image Processing and EXploration for Diverse Tissue Types
Mariya Mardamshina, Frederic Ballllosera Navarro, … Emma K. Lundberg·bioRxiv·May 4, 2025
- A SIMPLI (Single-cell Identification from MultiPLexed Images) approach for spatially resolved tissue phenotypingat single-cell resolution.
Michele Bortolomeazzi, Lucia Montorsi, … Francesca D. Ciccarelli·Nature CommunicationsPeer-reviewed·Feb 9, 2022
- SPACEc: A Streamlined, Interactive Python Workflow for Multiplexed Image Processing and Analysis
Yuqi Tan, Tim Noah Kempchen, … Garry P. Nolan·Nature CommunicationsPeer-reviewed·Nov 27, 2025
- An end-to-end workflow for multiplexed image processing and analysis
Jonas Windhager, Vito RT Zanotelli, … Nils Eling·Nature ProtocolsPeer-reviewed·Oct 10, 2023
- cytomapper: an R/Bioconductor package for visualisation of highly multiplexed imaging data
Nils Eling, Nicolas Damond, … Bernd Bodenmiller·BioinformaticsPeer-reviewed·Dec 10, 2020
- Spatialproteomics - an interoperable toolbox for analyzing highly multiplexed fluorescence image data
Matthias Meyer-Bender, Harald S. Vöhringer, … Wolfgang K. Huber·Nature MethodsPeer-reviewed·Jul 24, 2026