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0The paper introduces SpaMTP, an open-source software framework designed to bridge the gap between spatial metabolomics and transcriptomics. While these two fields offer distinct insights into cellular regulation, researchers previously lacked integrated tools to analyze their data simultaneously. Built upon the familiar Seurat architecture, this new platform offers advanced capabilities for metabolite annotation, joint clustering, and multimodal visualization. By streamlining the processing of mass spectrometry and gene expression data, SpaMTP enables a more comprehensive understanding of complex biological systems. The authors demonstrate its utility through various case studies, proving it is more effective at identifying metabolic pathways and tissue regions than existing software. Ultimately, this tool provides a standardized, user-friendly environment for exploring the spatial regulation of genes and metabolites together.
References:
Causer A, Lu T, Kriel J, et al. SpaMTP: integrative statistical analysis and visualization of spatial metabolomics and transcriptomics data[J]. Nature Methods, 2026: 1-6.
