Abstract

We introduce NMR-Onion, an open-source, computationally efficient algorithm based on Python and PyTorch, designed to facilitate the automatic deconvolution of 1D NMR spectra. NMR-Onion features two innovative time-domain models capable of handling asymmetric non-Lorentzian line shapes. Its core components for resolution-enhanced peak detection and digital filtering of user-specified key regions ensure precise peak prediction and efficient computation. The NMR-Onion framework includes three built-in statistical models, with automatic selection via the BIC criterion. Additionally, NMR-Onion assesses the repeatability of results by evaluating post-modeling uncertainty. Using the NMR-Onion algorithm helps to minimize excessive peak detection.
Original languageEnglish
Article numbere36998
JournalHeliyon
Volume10
Issue number17
Number of pages19
ISSN2405-8440
DOIs
Publication statusPublished - 2024

Keywords

  • Statistical evidence
  • Time domain models
  • Open source
  • Deconvolution
  • High sensitivity
  • Extensive overlaps
  • Computationally efficiency

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