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Published on: September 5, 2025
SpaMTP: integrative statistical analysis and visualization of spatial metabolomics and transcriptomics data
Andrew Causer1,2, Tianyao Lu3,4, Jurgen Kriel3,4
1QIMR Berghofer, Herston, Queensland, Australia.
Nature Methods
|July 31, 2026
Summary
We present SpaMTP, a new framework for integrating spatial omics data, including spatial metabolomics. This tool enhances the analysis of transcriptional, proteomic, and metabolic regulation in biological systems.
Area of Science:
- Spatial biology
- Multi-omics data integration
- Bioinformatics tools
Background:
- Spatially resolved multimodal data offer insights into biological regulation.
- Existing analytical tools for integrating spatial omics, especially spatial metabolomics, are limited.
Purpose of the Study:
- To develop an end-to-end framework, SpaMTP, for integrating spatial omics modalities.
- To provide enhanced analytical capabilities for spatial metabolomics and multimodal data.
Main Methods:
- Developed SpaMTP, a framework within the Seurat architecture.
- Implemented functions for metabolite annotation, joint clustering, enrichment tests, spatial alignment, and multimodal integration.
- Ensured seamless software interoperability and visualization capabilities.
Main Results:
- SpaMTP provides a unified approach for analyzing diverse spatial omics data.
- The framework facilitates metabolite annotation and joint analysis of different omics layers.
- Demonstrated the utility of SpaMTP across various biological systems.
Conclusions:
- SpaMTP addresses the limitations in analyzing integrated spatial omics data.
- The framework offers a comprehensive solution for exploring spatial regulation.
- SpaMTP is a valuable tool for advancing spatial multi-omics research.
