Rodin

Rodin streamlines metabolomics data analysis and visualization by integrating preprocessing, statistical testing, and pathway analysis into a unified Python-based workflow for processing large-scale mass spectrometry datasets.

Key Features:

• Feature Preprocessing: Rodin performs preprocessing of metabolic features from high-resolution mass spectrometry data.
• Statistical Testing: Rodin integrates statistical testing for metabolomics data analysis.
• Interactive Visualizations: Rodin generates interactive visualizations as part of its analytical outputs.
• Pathway Analysis: Rodin performs pathway analysis on metabolomics datasets.
• Parameter Tracking: Rodin tracks user-defined parameters within a single page during analysis.

Scientific Applications:

• Large-Scale Metabolomics Profiling: Rodin processes datasets containing hundreds of thousands of metabolic features from single experiments.
• Health Sciences Research: Rodin supports metabolomics applications across health sciences.

Methodology:

Rodin is implemented in Python and offers processing via a web interface or programming library.