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Bioinformatics Advance Access originally published online on May 12, 2005
Bioinformatics 2005 21(13):3043-3048; doi:10.1093/bioinformatics/bti476
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data

Age K. Smilde 1,2,*, Jeroen J. Jansen 1, Huub C. J. Hoefsloot 1, Robert-Jan A. N. Lamers 2, Jan van der Greef 2,3 and Marieke E. Timmerman 4

1Biosystems Data Analysis, Faculty of Sciences, University of Amsterdam Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands
2TNO Quality of life PO Box 360, 3700 AJ Zeist, The Netherlands
3Center for Medical Systems Biology, LACDR, Leiden University, Gorleaus Laboratories 2300 RA Leiden, The Netherlands
4Heymans Institute of Psychology, DPMG, University of Groningen Grote Kruisstraat 2/1, 9712 TS Groningen, The Netherlands

*To whom correspondence should be addressed.

Motivation: Datasets resulting from metabolomics or metabolic profiling experiments are becoming increasingly complex. Such datasets may contain underlying factors, such as time (time-resolved or longitudinal measurements), doses or combinations thereof. Currently used biostatistics methods do not take the structure of such complex datasets into account. However, incorporating this structure into the data analysis is important for understanding the biological information in these datasets.

Results: We describe ASCA, a new method that can deal with complex multivariate datasets containing an underlying experimental design, such as metabolomics datasets. It is a direct generalization of analysis of variance (ANOVA) for univariate data to the multivariate case. The method allows for easy interpretation of the variation induced by the different factors of the design. The method is illustrated with a dataset from a metabolomics experiment with time and dose factors.

Availability: M-files for MATLAB for the algorithm used in this research are available at: http://www-its.chem.uva.nl/research/pac/Software/ or at http://www.bdagroup.nl

Contact: asmilde{at}science.uva.nl


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