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bioRxiv · 10.1101/2025.06.04.657781

Cell-ECM Graphs: A Graph-Based Method for Joint Analysis of Cells and the Extracellular Matrix

Ghafoor, M.·Parkinson, J. E.·Sutherland, T. E.·Rattray, M.
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Abstract

Spatial proteomics technologies now profile cells and the extracellular matrix (ECM) together in situ. Yet analysis tools remain cell-centric, despite the ECM playing an essential role in health and disease. Here we present Mantpy, a framework that represents the ECM, and its interface with cells, as spatial graphs. Mantpy builds ECM graphs directly from matrix markers and links them with cell graphs for joint cell-ECM analysis, supporting graph statistics, explainable graph deep learning and visualisation. From a single ECM marker to multiplexed panels of ECM and cellular markers, Mantpy recovers layered tissue architecture in human intestine, resolves disease-associated matrix composition and organisation in infected mouse liver, and characterises cell-matrix associations in mouse lung. Released with ECM-inclusive datasets and interoperating with the scverse ecosystem, Mantpy extends the unit of spatial analysis beyond the cell, to the matrix that surrounds it.

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Ghafoor, M., Parkinson, J. E., Sutherland, T. E., Rattray, M.. 2025-06-04. Cell-ECM Graphs: A Graph-Based Method for Joint Analysis of Cells and the Extracellular Matrix. https://doi.org/10.1101/2025.06.04.657781

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