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

Author(s): Causer, A; Lu, T; Kriel, J; Moffet, JJD; Fitzgerald, CCJ; Newman, A; Vu, H; Tan, X; Vo, T; Cui, C; Narayana, VK; Whittle, JR; Best, SA; Freytag, S; Nguyen, Q;
Details: Publication Year 2026-08,Volume 23,Issue #8,Page 1501-1506
Journal Title: Nature Methods
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.
Publisher: Springer Nature
Keywords: *Metabolomics/methods; *Software; Spatial Transcriptomics; *Gene Expression Profiling/methods; Multiomics; Animals; *Transcriptome
Research Division(s): Personalised Oncology
PubMed ID: 42538468
Publisher's Version: https://doi.org/10.1038/s41592-026-03140-8
Open Access at Publisher's Site: https://doi.org/10.1038/s41592-026-03140-8
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2026-08-14 11:30:41

Last Modified: 2026-08-14 11:31:21