Gas chromatography coupled with mass spectrometry can provide an extensive overview of the metabolic state of a biological system. Analysis of raw mass spectrometry data requires powerful data processing software to generate interpretable results. Here we describe a data processing workflow to generate metabolite levels, mass isotopomer distribution, similarity and variability analysis of metabolites in a nontargeted manner, using stable isotope labeling. Using our data analysis software, no bioinformatic or programming background is needed to generate results from raw mass spectrometry data.
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| http://dx.doi.org/10.1007/978-1-0716-0159-4_2 | DOI Listing |
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