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Bioinformatics Advance Access published online on January 28, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp056
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Automated procedure for candidate compound selection in GC-MS metabolomics based on prediction of Kovats retention index

V.V. Mihaleva 1, H.A. Verhoeven 1,2, R.C.H. de Vos 1,2, R.D. Hall 1,2 and R.C.H.J. van Ham 1,3,*

1Applied Bioinformatics, PRI, Droevendaalsesteeg 1, Wageningen, The Netherlands, 2Centre for BioSystems Genomics (CBSG), Droevendaalsesteeg 1, Wageningen, The Netherlands, and 3Laboratory of Bioinformatics, Wageningen University, Dreijenlaan 3, Wageningen, The Netherlands

*To whom correspondence should be addressed. Dr. Roeland van Ham, E-mail: roeland.vanham{at}wur.nl


  Abstract

Motivation: Matching both the retention index (RI) and the mass spectrum of an unknown compound against a mass spectral reference library provides strong evidence for a correct identification of that compound. Data on retention indices are, however, available for only a small fraction of the compounds in such libraries. We propose a quantitative structure - retention index model that enables the ranking and filtering of putative identifications of compounds for which the predicted RI falls outside a predefined window.

Results: We constructed multiple linear regression and support vector regression (SVR) models using a set of descriptors obtained with a genetic algorithm as variable selection method. The SVR model is a significant improvement over previous models built for structurally diverse compounds as it covers a large range (360 to 4100) of RI values and gives better prediction of isomer compounds. The hit list reduction varied from 41% to 60% and depended on the size of the original hit list. Large hit lists were reduced to a greater extend compared to small hit lists.

Contact. roeland.vanham{at}wur.nl

Software availability. http://appliedbioinformatics.wur.nl/GC-MS

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Dr. Trey Ideker

Received on July 21, 2008; revised on December 11, 2008; accepted on January 24, 2009

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