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This research aims to develop a flexible toolbox for analyzing highly multiplexed immunofluorescence imaging data.

July 27, 2026Nature MethodsOpen Access

Spatialproteomics: an interoperable toolbox for analyzing highly multiplexed fluorescence image data

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This research aims to develop a flexible toolbox for analyzing highly multiplexed immunofluorescence imaging data.
Developed the 'spatialproteomics' Python package for image analysis.
Processed data from 132 patients' lymph nodes and B cell non-Hodgkin lymphomas.
Conducted end-to-end analysis including segmentation, image processing, and cell-type classification.
Successful processing of large imaging datasets, including Gigapixel whole-slide images.
Statistical characterization revealed significant variation in cell type composition across indolent and aggressive lymphomas.

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Randomized trial demonstrates the versatility of Spatialproteomics in analyzing protein levels in tissues, highlighting its potential applications.

Meyer-Bender et al. (2026) studied this question.

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Randomized trial demonstrates the versatility of Spatialproteomics in analyzing protein levels in tissues, highlighting its potential applications.