Journal of Biomolecular NMR

, Volume 55, Issue 4, pp 355–367

Nmrglue: an open source Python package for the analysis of multidimensional NMR data

Article

DOI: 10.1007/s10858-013-9718-x

Cite this article as:
Helmus, J.J. & Jaroniec, C.P. J Biomol NMR (2013) 55: 355. doi:10.1007/s10858-013-9718-x

Abstract

Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license.

Keywords

Nuclear magnetic resonance Solid-state NMR Data processing Data analysis Data visualization Python Open source 

Supplementary material

10858_2013_9718_MOESM1_ESM.pdf (194 kb)
Supplementary material 1 (PDF 194 kb)

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Chemistry and BiochemistryThe Ohio State UniversityColumbusUSA
  2. 2.Environmental Science DivisionArgonne National LaboratoryArgonneUSA

Personalised recommendations