Protomix: a Python package for ¹H-NMR metabolomics data preprocessing

Area of Science:

• Metabolomics
• Bioinformatics
• Computational Biology

Background:

• NMR-based metabolomics relies on advanced technological tools for data analysis.
• A significant lack of comprehensive, user-friendly preprocessing software exists in Python for this field.
• Efficient data preprocessing is crucial for advancing metabolomics research.

Purpose of the Study:

• To introduce Protomix, a novel Python package for NMR-based metabolomics.
• To provide automated, efficient, and user-friendly signal-preprocessing functionalities.
• To bridge the gap in available Python tools for metabolomics data handling.

Main Methods:

• Development of a Python package, Protomix, for metabolomics data preprocessing.
• Implementation of automated signal-preprocessing steps.
• Inclusion of data extraction, preprocessing, and interactive visualization features.
• Creation of a tutorial Jupyter notebook for 1D 1H-NMR data analysis.

Main Results:

• Protomix offers a comprehensive preprocessing pipeline compatible with diverse data analysis tools.
• The package streamlines the preprocessing phase in metabolomics studies.
• A tutorial demonstrates the analysis of 1D 1H-NMR data for prostate cancer and benign prostatic hyperplasia.

Conclusions:

• Protomix addresses the need for accessible and efficient preprocessing tools in NMR metabolomics.
• The package enhances the usability of metabolomics data analysis workflows.
• Protomix is available via GitHub and comprehensive documentation.