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Related Experiment Video

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Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
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OpenNAU: An open-source platform for normalizing, analyzing, and visualizing cancer untargeted metabolomics data.

Qingrong Sun1,2,3, Qingqing Xu1, Majie Wang4

  • 1Department of Pathology and Key Laboratory of Disease Proteomics of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, China.

Chinese Journal of Cancer Research = Chung-Kuo Yen Cheng Yen Chiu
|November 16, 2023
PubMed
Summary

This study introduces openNAU, an open-source platform for untargeted metabolomics data analysis. It ensures reproducible results for tumor mechanism research and metabolic marker discovery.

Keywords:
LAMP architectureUntargeted metabolomicsnormalizationreference metabolomicsshiny

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Area of Science:

  • Metabolomics
  • Bioinformatics
  • Computational Biology

Background:

  • Untargeted metabolomics is crucial for studying tumor mechanisms and identifying metabolic markers.
  • High-throughput spectrometric data presents significant data analysis challenges, from raw data extraction to differential metabolite identification.
  • Varied results arise from different analytical tools and parameter settings in untargeted metabolomics.

Purpose of the Study:

  • To establish an easily operated platform for untargeted metabolomics data analysis.
  • To achieve repeatable and reliable analysis results.
  • To address the challenges in processing and analyzing high-throughput metabolomics data.

Main Methods:

  • Developed a preprocessing system for raw data using the R language.
  • Built a cloud mass spectrometry data analysis system utilizing the LAMP (Linux+Apache+MySQL+PHP) architecture.
  • Constructed an open-source analysis software named openNAU.

Main Results:

  • openNAU software was created for untargeted metabolomics data analysis.
  • The software includes raw mass data extraction and quality control for identifying differential metabolic ion peaks.
  • A reference metabolomics database was established using public databases.

Conclusions:

  • A comprehensive analysis system platform for untargeted metabolomics was successfully established.
  • The platform offers a user-friendly interface for adding and updating analysis processes, simplifying complex analyses.
  • The open-source code is available for download, promoting accessibility and further development.