SpaMTP: integrative statistical analysis and visualization of spatial metabolomics and transcriptomics data.

Causer, Andrew; Lu, Tianyao; Kriel, Jurgen; Moffet, Joel J D; Fitzgerald, Christopher C J; Newman, Andrew; Vu, Hani; Tan, Xiao et al. · Nat Methods · 2026

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Abstract

Spatially resolved multimodal data enable the exploration of transcriptional, proteomic and metabolic regulation, yet analytical tools to integrate these spatial omics modalities, particularly spatial metabolomics, remain limited. We developed SpaMTP, an end-to-end framework that implements functions within a common Seurat architecture. It introduces analyses for metabolite annotation, joint clustering, enrichment tests, spatial alignment, multimodal integration, visualization and seamless software interoperability. Its utility is demonstrated across different biological systems.