Preliminary Comparison of Non-Fourier Methods for Spectrum Analysis of Nonuniformly Sampled NMR Data

Published

January 2, 2018

Author(s)

Mark W. Maciejewski, Hesam Dashti, Matthew Zambrello, Adam D. Schuyler, Mehdi Mobli, Hamid R. Eghbalnia, Frank Delaglio, Alan S. Stern, Jeffrey C. Hoch

Abstract

The advantages in resolution, sensitivity, and experiment time afforded by nonuniform sampling (NUS) in the indirect time dimensions of multidimensional NMR experiments has stimulated development of non-Fourier algorithms for spectrum analysis. Yet critical comparisons of various approaches have been elusive, in part because of the challenge of acquiring, configuring, and running the corresponding software packages, and because of the lack of quantitative metrics suitable for quantitative comparison of the results. The recent development of the NMRbox platform provides a unified environment specifically designed to facilitate interoperation among and critical comparison of multiple NMR software packages. Here we describe a preliminary comparison of 12 different non-Fourier methods applied to a common set of NUS data. Qualitative comparison reveals readily discernible differences among the results returned by the various packages. There is wide variation in the ability to suppress NUS artifacts, noise distributions, and fidelity to signal phase among the packages. This study demonstrates the special challenges posed by a critical comparison of non-Fourier methods and the utility of the NMRbox platform for facile comparisons of NMR software and the identification of best practices for improving spectral quality.

Citation

Journal of Biomolecular Nmr

Pub Type

Journals

Keywords

signal processing, spectrum analysis, non-Fourier, nonuniform sampling, compressed sensing

Citation

Maciejewski, M. , Dashti, H. , Zambrello, M. , Schuyler, A. , Mobli, M. , Eghbalnia, H. , Delaglio, F. , Stern, A. and Hoch, J. (2018), Preliminary Comparison of Non-Fourier Methods for Spectrum Analysis of Nonuniformly Sampled NMR Data, Journal of Biomolecular Nmr (Accessed December 10, 2023)