Processing DNP-NMR data has it’s own challenges. Some groups use an old Bruker console for data acquisition others use a Varian console, and then there is the occasional Magritek Kea hardware that is used. All these different spectrometers save data in different formats. In addition, sometimes EPR data needs to be process as well. Many research groups have developed their code , but it is often specifically tailored to their needs and can’t be easily adapted by other groups.
Over the last two years, Bridge12 in collaboration with the Lab of Prof. John Franck at Syracuse University and the Lab of Prof. Song-I Han at the University of California - Santa Barbara has developed a Python package for importing, processing and analyzing DNP-NMR data. DNPLab is an open-source package and the source code is hosted at GitHub, while the package itself can be easily installed from PyPi.
The package is authored by Timothy Keller, Thomas Casey, Yanxian Lin, John Franck, Thorsten Maly, and Songi Han.
The source code for the project is published here: DNPLab on GitHub
Some of the features of DNPLab are:
- Import DNP-NMR data in various formats (e.g. Bruker (TopSpin), Varian (Open/VnmrJ), Magritek (Prospa))
- Import EPR data in Xepr, WinEPR, or SpecMan4EPR format
- Process NMR data (appodization, resolution enhancement, Fourier transformation, phasing …)
- Calculate DNP enhancement factors, extract hydration dynamics information, generally analyze DNP-NMR data
- Create professional-looking figures
Under the hood, DNPLab uses the dnpdata class as a flexible data container for N-dimensional data. The dndpdate class stores data, axes, parameters and processing information in a single object. The dnpdata class integrates some concepts from, and designed for ongoing compatibility with, pySpecData, an object-oriented spectral data processing package developed by the Franck Lab at Syracuse University, with ongoing collaborations between the development teams at Bridge12 Technologies, Inc. and the Han Lab at University of California, Santa Barabara.
The documentation for DNPLab is hosted online and contains many examples to get you started. The package is constantly updated and its functionality is growing.
This work has been funded by the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH) under Grants GM116612 and GM126770.