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Scientific workflow managers in metabolomics: an overview.

Aswin Verhoeven1, Martin Giera, Oleg A Mayboroda

  • 1Center for Proteomics and Metabolomics, Leiden University Medical Center, Albinusdreef 2, 2333ZA, Leiden, The Netherlands. A.Verhoeven@lumc.nl.

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Summary

Scientific workflow managers enhance reproducibility in life sciences, particularly for metabolomics data analysis. This summary explores available workflow tools to aid researchers in achieving reliable results.

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Area of Science:

  • Life Sciences
  • Metabolomics
  • Bioinformatics

Background:

  • The scientific community faces a reproducibility crisis, emphasizing the need for transparent data processing and analysis.
  • Reproducibility in life sciences research is crucial for validating results and accelerating clinical applications.
  • While workflow managers are common in genomics, metabolomics traditionally relies more on scripts and standalone software.

Purpose of the Study:

  • To summarize and highlight the utility of scientific workflow managers for metabolomics data analysis.
  • To address the gap in adoption of workflow management tools within the metabolomics field.
  • To present available versatile workflow options for metabolomics.

Main Methods:

  • Literature review of scientific workflow management platforms.
  • Identification of platforms offering metabolomics-specific workflows.
  • Summary of features and applicability of identified platforms.

Main Results:

  • Scientific workflow managers offer significant potential for improving reproducibility in metabolomics.
  • KNIME and Galaxy platforms provide versatile workflow options for metabolomics analysis.
  • Despite traditional reliance on scripts, dedicated workflow solutions are emerging for metabolomics.

Conclusions:

  • Adopting scientific workflow managers can significantly enhance the reliability and reproducibility of metabolomics studies.
  • Researchers in metabolomics should consider utilizing platforms like KNIME and Galaxy for robust data analysis.
  • Further exploration and adoption of workflow management tools are recommended for the metabolomics community.