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SMAnalyst: A Web Server for Spatial Metabolomic Data Analysis and Annotation.

Zhanlong Mei1, Xiaolian Ning2, Haoke Deng1

  • 1BGI Genomics, Shenzhen 518083, China.

Biomolecules
|November 27, 2025
PubMed
Summary
This summary is machine-generated.

SMAnalyst is a new open-source platform that simplifies spatial metabolomics analysis. It integrates quality control, metabolite identification, and differential analysis, making complex data accessible.

Keywords:
differential analysismetabolite annotationquality controlspatial metabolomicsspatial pattern discoveryweb-based platform

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Area of Science:

  • * Spatial metabolomics and its role in understanding tissue metabolic heterogeneity.

Background:

  • * Current spatial metabolomics analysis is hampered by fragmented tools and a lack of integrated, open-source GUI software.
  • * A comprehensive workflow covering quality control, preprocessing, identification, pattern, and differential analysis is missing.

Purpose of the Study:

  • * To develop SMAnalyst, an integrated, open-source, web-based platform for spatial metabolomics data analysis.
  • * To provide a user-friendly GUI that lowers the barrier to entry for complex spatial metabolomics workflows.

Main Methods:

  • * Development of an integrated platform consolidating multi-dimensional data quality assessment.
  • * Implementation of a metabolite annotation scoring system based on mass accuracy, isotopic similarity, and adduct evidence.
  • * Inclusion of dual-dimension spatial pattern discovery (metabolite co-expression, pixel clustering) and flexible differential analysis.

Main Results:

  • * SMAnalyst offers a unified solution, eliminating the need for tool switching and advanced computational skills.
  • * The platform was successfully tested on a mouse brain dataset, efficiently handling large-scale data (>14,000 pixels, >3000 ion peaks).
  • * Demonstrated capability in multi-dimensional data quality assessment, metabolite annotation, and spatial pattern discovery.

Conclusions:

  • * SMAnalyst effectively addresses the critical gap in integrated analytical solutions for spatial metabolomics.
  • * The platform significantly lowers the analysis barrier, promoting wider adoption of spatial metabolomics.
  • * Provides a comprehensive, user-friendly tool for analyzing metabolic heterogeneity in biological tissues.