Preprints
https://doi.org/10.5194/mr-2021-59
https://doi.org/10.5194/mr-2021-59

  09 Aug 2021

09 Aug 2021

Review status: this preprint is currently under review for the journal MR.

NUScon: A community-driven platform for quantitative evaluation of nonuniform sampling in NMR

Yulia Pustovalova1, Frank Delaglio2, D. Levi Craft1, Haribabu Arthanari3,4, Ad Bax5, Martin Billeter6, Mark J. Bostock7, Hesam Dashti8, D. Flemming Hansen9, Sven G. Hyberts4, Bruce A. Johnson10, Krzysztof Kazimierczuk11, Hengfa Lu12, Mark Maciejewski1, Tomas M. Miljenovic13, Mehdi Mobli13, Daniel Nietlispach7, Vladislav Orekhov6, Robert Powers14, Xiaobo Qu15, Scott Anthony Robson16, David Rovnyak17, Gerhard Wagner4, Jinfa Ying5, Matthew Zambrello1, Jeffrey C. Hoch1, David L. Donoho18, and Adam D. Schuyler1 Yulia Pustovalova et al.
  • 1Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030, USA
  • 2Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, MD 20850, USA
  • 3Department of Cancer Biology, Dana Farber Cancer Institute, Boston, MA, 02215, USA
  • 4Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
  • 5Laboratory of Chemical Physics, NIDDK, National Institutes of Health, Bethesda, MD 20892, USA
  • 6Department of Chemistry and Molecular Biology, University of Gothenburg, Box 465, Gothenburg 405 30, Sweden
  • 7Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
  • 8Division of Preventive Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, USA
  • 9Department of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, UK
  • 10Structural Biology Initiative, CUNY Advanced Science Research Center, New York, NY 10031, USA
  • 11Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland
  • 12Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
  • 13Centre for Advanced Imaging, The University of Queensland, 4072 St Lucia, Queensland, Australia
  • 14Department of Chemistry and Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
  • 15Department of Electronic Science, Biomedical Intelligent Cloud R&D Center, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
  • 16Department of Molecular and Cellular Biochemistry, Indiana University, Bloomington, IN 47405, USA
  • 17Department of Chemistry, Bucknell University, Lewisburg, PA 17837, USA
  • 18Department of Statistics, Stanford University, Stanford, CA 94305, USA

Abstract. Although the concepts of non-uniform sampling (NUS) and non-Fourier spectral reconstruction in multidimensional NMR began to emerge four decades ago (Bodenhausen and Ernst, 1981; Barna and Laue, 1987), it is only relatively recently that NUS has become more commonplace. Advantages of NUS include the ability to tailor experiments to reduce data collection time and to improve spectral quality, whether through detection of closely spaced peaks (i.e., “resolution”) or peaks of weak intensity (i.e., “sensitivity”). Wider adoption of these methods is the result of improvements in computational performance, a growing abundance and flexibility of software, support from NMR spectrometer vendors, and the increased data sampling demands imposed by higher magnetic fields. However, the identification of best practices still remains a significant and unmet challenge. Unlike the discrete Fourier transform, non-Fourier methods used to reconstruct spectra from NUS data are nonlinear, depend on the complexity and nature of the signals, and lack quantitative or formal theory describing their performance. Seemingly subtle algorithmic differences may lead to significant variabilities in spectral qualities and artifacts. A community-based critical assessment of NUS challenge problems has been initiated, called the “Nonuniform Sampling Contest” (NUScon), with the objective to determine best practices for processing and analyzing NUS experiments. We address this objective by constructing challenges from NMR experiments that we inject with synthetic signals and we process these challenges using workflows submitted by the community. In the initial rounds of NUScon our aim is to establish objective criteria for evaluating the quality of spectral reconstructions. We present here a software package for performing the quantitative analyses and we present the results from the first two rounds of NUScon. We discuss the challenges that remain and present a road-map for continued community-driven development with the ultimate aim to provide best practices in this rapidly evolving field. The NUScon software package and all data from evaluating the challenge problems are hosted on the NMRbox platform.

Yulia Pustovalova et al.

Status: open (until 25 Sep 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Yulia Pustovalova et al.

Yulia Pustovalova et al.

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Short summary
We present the on-going work of a large, community initiative to establish standards for the processing of nonuniformly sampled NMR experiments. The NUScon software, contest, and archive of spectral evaluation data provide a comprehensive platform for addressing the most challenging questions related to NUS experiments. We will run annual contests and generate a database of results, which will empower us to guide the NUS community towards a set of best practices.