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MetaboLab - advanced NMR data processing and analysis for metabolomics

Ludwig, Christian and Günther, Ulrich L (2011) MetaboLab - advanced NMR data processing and analysis for metabolomics. BMC Bioinformatics, 12 (1). p. 366. ISSN 1471-2105

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URL of Published Version: http://dx.doi.org/10.1186/1471-2105-12-366

Identification Number/DOI: doi:10.1186/1471-2105-12-366

Background
Despite wide-spread use of Nuclear Magnetic Resonance (NMR) in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis.

Results
Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra) is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments.

Conclusions
The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.

Type of Work:Article
Date:13 December 2011 (Publication)
School/Faculty:Colleges (2008 onwards) > College of Life & Environmental Sciences
Department:School of Cancer Sciences
Subjects:Q Science (General)
QR Microbiology
R Medicine (General)
Institution:University of Birmingham
Copyright Holders:BioMed Central
ID Code:894
Refereed:YES
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