Source-linked AI summary
NMRProcFlow: A graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics
Daniel Jacob, Catherine Deborde, Marie Lefebvre, Mickael Maucourt, Anick Moing
TL;DR
NMRProcFlow addresses programming skill barriers in NMR-based metabolomics while supporting statistical analysis. It provides interactive visualization of spectra and experimental factor levels, and has been used successfully in collaborative work.
Problem
NMRProcFlow addresses the programming skill barrier in applying expertise to NMR-based metabolomics and the need to connect spectra with statistical analysis.
Method
NMRProcFlow provides interactive spectral viewing with experimental factor levels across metabolic fingerprinting and targeted metabolomics workflows, using minimal user input without arbitrary parameters or reference spectra.
Results
NMRProcFlow has been used successfully in a previous collaborative work.
Takeaways & Limitations
Visualizing factor levels within spectra creates links between experimental design and subsequent statistical analyses, facilitating interactions between biologists and NMR spectroscopists.
Takeaways & Limitations
The current version accepts only pre-processed raw spectra in Bruker format, and automatic phasing still requires manual input.
Abstract
from arXiv · showhide
Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks, and so far the best way is to proceed interactively with a spectra viewer. NMRProcFlow is a graphical and interactive 1D NMR (1H \& 13C) spectra processing tool dedicated to metabolic fingerprinting and targeted metabolomic, covering all spectra processing steps including baseline correction, chemical shift calibration, alignment. It does not require programming skills. Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.
Keywords
NMRProcFlow addresses NMR-based metabolomics through NMR viewing and spectra processing in a graphical user interface.
- The paper focuses on NMR-based metabolomics, NMR viewing, spectra processing, and graphical user interfaces.
Introduction
High-throughput OMICS generates growing data volumes, motivating more automated processing while preserving users’ ability to apply domain expertise without programming skills.
- High-throughput analytical techniques in OMICS generate growing volumes of data.
- The processing trend is to automate data handling while retaining expert know-how.
- Users should be able to apply their expertise without a programming-skill barrier.
Implementation
NMRProcFlow combines open-source components with graphical, client-server processing and online or local deployment options for NMR spectra.
- NMRspec was implemented mainly with open-source software, including R, C++, Rcpp, Rnmr1D, and R Shiny.
- NMRviewer uses a client-server architecture with binary spectral data and PNG image generation to minimize reading, writing, and transfer costs.
- NMRProcFlow is available online as a web tool.
- The tool provides advanced 1D NMR processing for users with or without expertise and avoids requiring local software installation.
- Virtual appliances compatible with VMware and Oracle VirtualBox support local setup and confidential-data security.
Results and Discussion
NMRProcFlow integrates interactive spectral visualization with factor-level information and processing workflows for metabolic fingerprinting and targeted metabolomics. It supports region-specific choices, adaptive binning, quality filtering, quantification exports, and reusable batch workflows, while retaining input-format and preprocessing constraints.
- Results and Discussion: Visualizing experimental factor levels within the spectra viewer is a central strength of NMRProcFlow.
- Results and Discussion: The tool links spectra viewing with experimental design and subsequent statistical analyses, supporting interaction between biologists and NMR spectroscopists.
- Results and Discussion: Users can choose processing methods by ppm region and apply visualization or alignment to full spectra sets or factor-level subsets.
- Results and Discussion: The current version accepts only pre-processed raw spectra in Bruker format, with broader input-format support planned.
- Results and Discussion: NMRProcFlow supports metabolic fingerprinting and targeted metabolomics across the workflow from spectral data to the output data matrix.
- Results and Discussion: Adaptive Intelligent Binning addresses information loss and artifacts from peak shifts by recursively identifying bin edges with minimal user input.
- Results and Discussion: Signal-to-Noise ratio filtering can be applied during computation or at output, and this capability was used successfully in prior collaborative work.
- Results and Discussion: Experts can create reusable workflows and process similar, well-mastered use cases in batch mode after interactively building a workflow on a subset.
Figure Captions
The figures depict NMRProcFlow as an interactive, visualization-based workflow for 1D NMR spectra processing, implemented through two applications.
- Figure 1 presents the workflow for interactive 1D NMR spectra processing through a spectra-visualization interface.
- Figure 2 shows the NMRProcFlow implementation divided into two applications.
Supplementary Information
The online documentation supplements the article with detailed feature descriptions, issue-specific guidance, examples, and workflow resources.
- The online documentation describes NMRProcFlow features and provides information on issues not detailed in the article.
- Supplementary resources demonstrate spectra alignment using Least-Square and Parametric Time Warping methods.
- Examples cover global and local baseline correction methods.
- Targeted metabolomics resources include a quantification spreadsheet workbook.
- Resources explain intelligent bucketing and metabolomic fingerprinting.
- Supplementary material documents signal-to-noise ratio assessment and batch-mode workflow replay.