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A Strategy for Identifying Differences in Large Series of Metabolomic Samples Analyzed by GC/MS
journal contribution
posted on 2004-03-15, 00:00 authored by Pär Jonsson, Jonas Gullberg, Anders Nordström, Miyako Kusano, Mariusz Kowalczyk, Michael Sjöström, Thomas MoritzIn metabolomics, the purpose is to identify and quantify
all the metabolites in a biological system. Combined gas
chromatography and mass spectrometry (GC/MS) is one
of the most commonly used techniques in metabolomics
together with 1H NMR, and it has been shown that more
than 300 compounds can be distinguished with GC/MS
after deconvolution of overlapping peaks. To avoid having
to deconvolute all analyzed samples prior to multivariate
analysis of the data, we have developed a strategy for rapid
comparison of nonprocessed MS data files. The method
includes baseline correction, alignment, time window
determinations, alternating regression, PLS-DA, and identification of retention time windows in the chromatograms
that explain the differences between the samples. Use of
alternating regression also gives interpretable loadings,
which retain the information provided by m/z values that
vary between the samples in each retention time window.
The method has been applied to plant extracts derived
from leaves of different developmental stages and plants
subjected to small changes in day length. The data show
that the new method can detect differences between the
samples and that it gives results comparable to those
obtained when deconvolution is applied prior to the
multivariate analysis. We suggest that this method can be
used for rapid comparison of large sets of GC/MS data,
thereby applying time-consuming deconvolution only to
parts of the chromatograms that contribute to explain the
differences between the samples.