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Bioinformatics. 2013 Jan 15;29(2):281-3. doi: 10.1093/bioinformatics/bts674. Epub 2012 Nov 17.

mzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data.

Author information

1
College of Medical Veterinary and Life Sciences, Institute of Molecular Cell and Systems Biology, University of Glasgow, Glasgow G12 8QQ, UK.

Abstract

MOTIVATION:

Stable isotope-labelling experiments have recently gained increasing popularity in metabolomics studies, providing unique insights into the dynamics of metabolic fluxes, beyond the steady-state information gathered by routine mass spectrometry. However, most liquid chromatography-mass spectrometry data analysis software lacks features that enable automated annotation and relative quantification of labelled metabolite peaks. Here, we describe mzMatch-ISO, a new extension to the metabolomics analysis pipeline mzMatch.R.

RESULTS:

Targeted and untargeted isotope profiling using mzMatch-ISO provides a convenient visual summary of the quality and quantity of labelling for every metabolite through four types of diagnostic plots that show (i) the chromatograms of the isotope peaks of each compound in each sample group; (ii) the ratio of mono-isotopic and labelled peaks indicating the fraction of labelling; (iii) the average peak area of mono-isotopic and labelled peaks in each sample group; and (iv) the trend in the relative amount of labelling in a predetermined isotopomer. To aid further statistical analyses, the values used for generating these plots are also provided as a tab-delimited file. We demonstrate the power and versatility of mzMatch-ISO by analysing a (13)C-labelled metabolome dataset from trypanosomal parasites.

AVAILABILITY:

mzMatch.R and mzMatch-ISO are available free of charge from http://mzmatch.sourceforge.net and can be used on Linux and Windows platforms running the latest version of R.

CONTACT:

rainer.breitling@manchester.ac.uk.

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
23162054
PMCID:
PMC3546800
DOI:
10.1093/bioinformatics/bts674
[Indexed for MEDLINE]
Free PMC Article
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