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MSClust: a tool for unsupervised mass spectra extraction of chromatography-mass spectrometry ion-wise aligned data

Authors
Journal
Metabolomics
1573-3882
Publisher
Springer-Verlag
Publication Date
Volume
8
Issue
4
Identifiers
DOI: 10.1007/s11306-011-0368-2
Keywords
  • Short Communication
Disciplines
  • Computer Science

Abstract

Mass peak alignment (ion-wise alignment) has recently become a popular method for unsupervised data analysis in untargeted metabolic profiling. Here we present MSClust—a software tool for analysis GC–MS and LC–MS datasets derived from untargeted profiling. MSClust performs data reduction using unsupervised clustering and extraction of putative metabolite mass spectra from ion-wise chromatographic alignment data. The algorithm is based on the subtractive fuzzy clustering method that allows unsupervised determination of a number of metabolites in a data set and can deal with uncertain memberships of mass peaks in overlapping mass spectra. This approach is based purely on the actual information present in the data and does not require any prior metabolite knowledge. MSClust can be applied for both GC–MS and LC–MS alignment data sets. Electronic supplementary material The online version of this article (doi:10.1007/s11306-011-0368-2) contains supplementary material, which is available to authorized users.

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