Motivation: Labelling experiments in biology usually make use of isotopically-enriched substrates, with the two most commonly employed isotopes for metabolism being 2 H and 13 C. At the end of the experiment some metabolites will have incorporated the labelling isotope, to a degree that depends on the metabolic turnover. In order to propose a meaningful biological interpretation, it is necessary to estimate the amount of labelling, and one possible route is to exploit the fact that MS isotopic patterns reflect the isotopic distributions. Results: We developed the IsotopicLabelling R package, a tool able to extract and analyse isotopic patterns from liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-MS (GC-MS) data relative to labelling experiments. This package estimates the isotopic abundance of the employed stable isotope (either 2 H or 13 C) within a specified list of analytes. Availability: The IsotopicLabelling R package is freely available at https://github.com/RuggeroFerrazza/IsotopicLabelling
Ferrazza, R.; Griffin, J.L.; Guella, G.; Franceschi, P. (2017). IsotopicLabelling: an R package for the analysis of MS isotopic patterns of labelled analytes. BIOINFORMATICS, 33 (2): 300-302. doi: 10.1093/bioinformatics/btw588 handle: http://hdl.handle.net/10449/33801
Citation: | Ferrazza, R.; Griffin, J.L.; Guella, G.; Franceschi, P. (2017). IsotopicLabelling: an R package for the analysis of MS isotopic patterns of labelled analytes. BIOINFORMATICS, 33 (2): 300-302. doi: 10.1093/bioinformatics/btw588 handle: http://hdl.handle.net/10449/33801 |
Internal authors: | Franceschi, Pietro (Last) |
Organization unit: | Unit of Computational Biology # CRI |
Authors: | Ferrazza, R.; Griffin, J.L.; Guella, G.; Franceschi, P. |
Title: | IsotopicLabelling: an R package for the analysis of MS isotopic patterns of labelled analytes |
Journal: | BIOINFORMATICS |
Issue Date: | 2017 |
Scientific Disciplinary Area: | Settore CHIM/01 - Chimica Analitica |
Keywords ENG: | Mass spectrometry Data analysis Isotope analysis |
Language: | English |
IF: | With Impact Factor ISI |
Publication status: | Published |
Nature of content: | Articolo in rivista/Article |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1093/bioinformatics/btw588 |
Appears in Collections: | 01 - Journal article |
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