Nextflow4MS-DIAL: A Reproducible Nextflow-Based Workflow for Liquid Chromatography-Mass Spectrometry Metabolomics...

Area of Science:

• Metabolomics
• Computational Biology
• Bioinformatics

Background:

• Reproducibility in untargeted metabolomics data processing is a significant challenge.
• Software limitations and complex manual steps contribute to inconsistencies.
• Automated solutions are needed to improve data processing reliability.

Purpose of the Study:

• To develop a reproducible workflow for liquid chromatography-mass spectrometry (LC-MS) metabolomics data processing.
• To address the challenges of software limitations and manual data handling in metabolomics.
• To enhance computational reproducibility and facilitate collaborative research.

Main Methods:

• Developed Nextflow4MS-DIAL, an automated workflow for LC-MS metabolomics data processing.
• Utilized software containerization for computational reproducibility.
• Validated the workflow with publicly available data from MetaboLights (MTBLS733).

Main Results:

• Nextflow4MS-DIAL automates LC-MS data processing, minimizing human errors.
• The workflow ensures computational reproducibility through containerization.
• Demonstrated compatibility with Unix-like systems and multiple job schedulers.

Conclusions:

• Nextflow4MS-DIAL significantly improves reproducibility in untargeted metabolomics data processing.
• The workflow enhances data analysis reliability and supports collaborative research efforts.
• Nextflow4MS-DIAL offers a flexible and user-friendly solution for LC-MS data processing.