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SMQVP: A Web Application for Spatial Metabolomics Quality Visualization and Processing
Zhanlong Mei1, Wan Sun1, Yun Zhao1
1BGI Genomics, Shenzhen 518083, China.
Metabolites
|June 25, 2025
Summary
Spatial metabolomics data quality is improved with SMQVP v1.0 software. This tool systematically assesses and preprocesses data, enhancing the reliability of biological insights from spatial metabolomics studies.
Area of Science:
- * Spatial metabolomics
- * Computational biology
- * Data science
Background:
- * Spatial metabolomics offers spatially resolved metabolite mapping for biological insights.
- * Data quality control and preprocessing are critical bottlenecks impacting reliability.
Purpose of the Study:
- * Introduce Spatial Metabolomics data Quality Visualization and Processing (SMQVP v1.0).
- * Provide a user-friendly graphical interface for systematic quality assessment and preprocessing of spatial metabolomics data.
Main Methods:
- * SMQVP v1.0 incorporates eight modules for quality visualization and evaluation.
- * Modules include background consistency, noise ion filtering, and intensity distribution analysis.
- * Identification of isotopic and adduct ions is also included.
Main Results:
- * SMQVP effectively identified and removed noise signals in AFADESI-based mouse brain data.
- * Preprocessing with SMQVP improved clustering accuracy, better reflecting tissue morphology.
- * Enhanced data integrity led to more robust downstream analyses.
Conclusions:
- * SMQVP is the first systematic approach for spatial metabolomics quality visualization.
- * Offers an accessible solution for enhancing data integrity and mitigating technical noise.
- * Improves the reliability and robustness of spatial metabolomics findings.
