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Updated: Mar 25, 2026

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
Published on: October 31, 2025
SMIntegration: A web tool for comprehensive spatial metabolomics and transcriptomics integrated analysis and
Haoke Deng1, Xiaolian Ning2, Xun Lin1
1Department of Mass Spectrometry, BGI, No. 146, Beishan Road, Yantian District, Shenzhen 518083, Guangdong Province, China.
Abstract:
Current tools for spatial omics analysis often face challenges in performing integrated transcriptomics and metabolomics analysis, in-depth biological interpretation, and user-friendly operation. To address this, we developed SMIntegration, the first web-based graphical platform designed specifically for integrated spatial metabolomics and transcriptomics analysis. Built with R/Shiny and deployed using Docker containerization, the platform provides a complete integration workflow, starting from pre-processed spatial features through to functional annotation. Its core functions include (1) automated and interactive spatial registration; (2) cross-modal spatial pattern recognition; (3) flexible differential analysis of genes and mass features based on clustering results, user-defined regions, or cell type annotations; and (4) group-specific gene-metabolite network construction and interactive visualization. Using adjacent mouse brain coronal sections (Stereo-seq transcriptomics and AFADESI-MS metabolomics) as an example, SMIntegration successfully identified both the periaqueductal gray and subcommissural organ, which were missed by single-modality clustering. Cell type analysis revealed an association between astrocyte-enriched GABA metabolism and Slc6a11, while a comparison between the cornu ammonis region and the midbrain periaqueductal gray dissected glutamatergic and endogenous cannabinoid signaling pathway modules. With a zero-code interface, SMIntegration enables a wide range of researchers to deeply explore gene-metabolite interaction mechanisms within microenvironments during development, homeostasis, and disease.

