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Updated: Feb 7, 2026
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Mining Spatial Transcriptomics Datasets using DeepSpaceDB
Published on: September 5, 2025
781
MANTIS: Analytics toolkit for spatial metabolomics with matching spatial transcriptomics data
Yu Hao1, Yeojin Kim1, Bhavay Aggarwal1
1The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Biorxiv : the Preprint Server for Biology
|February 6, 2026
Summary
MANTIS is a new tool that analyzes spatial metabolomics and spatial transcriptomics data together. It reveals metabolite patterns and gene-metabolite links, improving our understanding of tissue function.
Area of Science:
- Multi-omics spatial analysis
- Computational biology
- Biotechnology
Background:
- Spatial Metabolomics (SM) and Spatial Transcriptomics (ST) are powerful technologies for analyzing tissue function.
- Integrating SM and ST data enhances understanding of metabolic and gene expression patterns.
- Current tools offer limited capabilities for exploring relationships between SM and ST data.
Purpose of the Study:
- To introduce MANTIS, a computational tool for analyzing paired SM and ST data.
- To discover metabolite spatial distribution patterns and gene-metabolite relationships.
- To provide a unified framework for spatial omics data analysis with rigorous statistical testing.
Main Methods:
- MANTIS analyzes aligned SM+ST profiles, optionally with spatial domain or cell type information.
- It employs specialized permutation tests to assess statistical significance, controlling for spatial autocorrelation.
- Utilizes spatial cross-correlation and partial correlation statistics for quantifying gene-metabolite associations.
Main Results:
- MANTIS successfully identified metabolite spatial patterns and gene-metabolite relationships across diverse datasets.
- The tool demonstrated superior specificity in detecting patterns and associations compared to existing methods.
- MANTIS effectively disentangles various sources contributing to spatial patterns and correlations.
Conclusions:
- MANTIS is the first toolkit to integrate spatial metabolomics, spatial transcriptomics, cell type, and spatial domain information.
- It provides a robust framework for hypothesis testing in spatial omics research.
- The tool enhances the discovery of biological insights from multi-omics spatial data.
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