Mantpy: a framework for extracellular matrix analysis in spatial proteomics

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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 frame-work 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. Mantpy extends from a single ECM marker to multiplexed cell–ECM panels. It recovers layered tissue architecture in the intestine from collagen IV alone, quantifies infection-associated ECM remodelling in mouse liver, and relates cells to the surrounding matrix in mouse lung, where cellular context recovers synthetically corrupted matrix labels. Released with ECM-inclusive datasets and interoperating with the scverse ecosystem and pytorch geometric. Mantpy brings the matrix into spatial analysis alongside the cell.

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