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Rodin: a streamlined metabolomics data analysis and visualization tool
Boris Minasenko1, Dongxue Wang1, Piera Cirillo2
1Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, United States.
Bioinformatics Advances
|April 28, 2025
Summary
Rodin is a new Python application that simplifies metabolomics data analysis. It offers fast processing, integrated tools, and user-friendly features for researchers.
Area of Science:
- Metabolomics
- Bioinformatics
- Computational Biology
Background:
- High-resolution mass spectrometry has advanced metabolomics.
- Analyzing large metabolomics datasets is complex.
- Existing tools can be difficult to access and integrate.
Purpose of the Study:
- To develop a user-friendly application for streamlining metabolomics data analysis.
- To integrate multiple analysis stages into a single platform.
- To enhance accessibility and analytic throughput for metabolomics researchers.
Main Methods:
- Developed Rodin, a Python-based application.
- Integrated feature preprocessing, statistical testing, and pathway analysis.
- Provided a web interface and a programming library for accessibility.
Main Results:
- Rodin offers fast and efficient processing of large metabolomics datasets.
- The application integrates multiple analysis stages with parameter tracking.
- Rodin enhances user-friendliness and ease of access compared to other tools.
Conclusions:
- Rodin streamlines metabolomics workflows for users of all skill levels.
- The application promotes reproducible and efficient data analysis.
- Rodin enhances the accessibility of advanced metabolomics tools.
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