speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification

Area of Science:

• Metabolomics
• Analytical Chemistry
• Bioinformatics

Background:

• Nuclear Magnetic Resonance (NMR) spectroscopy is a primary metabolomics platform alongside LC-MS.
• Current NMR data processing relies on commercial software, often involving tedious user interventions.
• Previous work introduced speaq for NMR spectral alignment and quantitation.

Purpose of the Study:

• To present speaq 2.0, a completely revised framework for automated 1D NMR spectral analysis.
• To offer a faster, more user-friendly, and less interactive data processing workflow.
• To facilitate robust and high-throughput metabolomics using 1D NMR data.

Main Methods:

• Utilizes wavelets for efficient raw spectra summarization with minimal information loss.
• Implements a workflow starting with peak-picking followed by grouping, bypassing the binning step.
• Generates a feature-sample-value matrix compatible with multivariate statistical functions and other analysis methods.

Main Results:

• speaq 2.0 provides an automated and efficient workflow for 1D NMR data analysis.
• The framework minimizes user interaction and speeds up the processing pipeline.
• Benchmarking was performed using simulated and publicly available datasets.

Conclusions:

• speaq 2.0 offers a robust and high-throughput solution for NMR-based metabolomics.
• The tool is compatible with other NMR frameworks and LC-MS workflows.
• speaq 2.0 is freely available as an R package on CRAN and GitHub.