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Data normalization strategies in metabolomics: Current challenges, approaches, and tools.

Biswapriya B Misra1

  • 1Center for Precision Medicine, Section of Molecular Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA.

European Journal of Mass Spectrometry (Chichester, England)
|April 12, 2020
PubMed
Summary

Data normalization is crucial for accurate metabolomics. This review covers statistical methods and new software tools to improve mass spectrometry and spectroscopy data quality for reliable biological insights.

Keywords:
Metabolitenormalizationquantificationsamplesoftware

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Area of Science:

  • Metabolomics
  • Bioinformatics
  • Analytical Chemistry

Background:

  • Quantitative metabolomics relies on accurate data analysis.
  • Improper data normalization in mass spectrometry and spectroscopy leads to erroneous results.
  • This can hinder applications in healthcare and biological research.

Purpose of the Study:

  • To review existing and novel approaches for metabolomics data normalization.
  • To highlight recent software tools that facilitate data normalization.
  • To address the challenge of achieving reliable quantitative metabolomics data.

Main Methods:

  • Literature review of statistical normalization approaches.
  • Summary of sample-based and data-based normalization strategies.
  • Introduction of recently developed software tools for metabolomics data normalization.

Main Results:

  • Multiple statistical methods and software tools exist for metabolomics data normalization.
  • New dedicated software tools have emerged to address normalization challenges.
  • A comprehensive overview of current normalization techniques is provided.

Conclusions:

  • Effective data normalization is essential for valid metabolomics research.
  • The availability of diverse tools aids researchers in selecting appropriate normalization strategies.
  • Advancements in normalization methods improve the reliability of metabolomics data for various applications.