rNMR

rNMR applies an ROI-based analysis to visualize, identify, and quantify metabolites across multiple one- and two-dimensional nuclear magnetic resonance (NMR) spectra using user-defined chemical shift ranges.

Key Features:

• Region of Interest (ROI)-Based Analysis: Uses ROIs that encompass all underlying NMR data within user-defined chemical shift ranges instead of relying on peak lists.
• Dynamic ROI Adjustment: Allows adjustment of ROI boundaries to maintain consistent analysis of signals corresponding to assigned atoms across a dataset.
• Simultaneous Multi-Spectrum Visualization: Supports simultaneous viewing of metabolite signals across up to hundreds of spectra for comparative analysis.
• Robust Quantification Support: Enables quantification of NMR signals via inspection and analysis of ROIs to derive measurements of metabolite signals.
• Time Efficiency: Streamlines analysis workflows to reduce the time required for processing complex NMR datasets.
• Transparent Data Archiving: Archives analysis results in a compact, transparent format that enables examination and evaluation by other researchers.

Scientific Applications:

• Metabolite identification and quantification: Facilitates identification and quantification of metabolites across multiple one- and two-dimensional NMR spectra in metabolomics studies.
• Comparative metabolomics and biomarker discovery: Enables comparative analysis across large datasets to support exploration of metabolic pathways and biomarker identification.

Methodology:

rNMR employs an ROI-based approach contrasting with traditional peak-list methods, focusing on user-defined chemical shift ranges that encompass underlying NMR data and permitting dynamic adjustment of ROI boundaries for analysis across multiple spectra.