A Likelihood Ratio Test for Differential Metabolic Profiles in Multiple Intensity Measurements

Authors:
Frank Klawonn;Claudia Choi;Beatrice Benkert;Bernhard Thielen;Richard Münch;Max Schobert;Dietmar Schomburg;Dieter Jahn
Affiliations:
Department of Computer Science, University of Applied Sciences Braunschweig /Wolfenbüttel, Salzdahlumer Str. 46/48, 38302 Wolfenbüttel, Germany;Institute of Microbiology, Technical University of Braunschweig, Spielmannstraße 7, 38106 Braunschweig, Germany;Institute of Microbiology, Technical University of Braunschweig, Spielmannstraße 7, 38106 Braunschweig, Germany;Institute of Biochemistry, University of Köln, Zülpicher Straße 47, 50674 Köln, Germany;Institute of Microbiology, Technical University of Braunschweig, Spielmannstraße 7, 38106 Braunschweig, Germany;Institute of Microbiology, Technical University of Braunschweig, Spielmannstraße 7, 38106 Braunschweig, Germany;Institute of Biochemistry, University of Köln, Zülpicher Straße 47, 50674 Köln, Germany;Institute of Microbiology, Technical University of Braunschweig, Spielmannstraße 7, 38106 Braunschweig, Germany
Venue:
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Year:
2007

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Abstract

High throughput technologies like transcriptomics using DNA arrays or metabolomics employing a combination of gas chromatography with mass spectrometry provide valuable information about cellular processes. However, the measurements are often highly corrupted with noise of the experimental data which makes it sometimes difficult to draw reliable conclusions. Therefore, suitable statistical methods are needed for the evaluation of the experimental data to distinguish changes caused by biological phenomena from random variations due to noise. This paper introduces a likelihood ratio test to multiple metabolome measurements. The method was tested to differentiate differential metabolite compositions obtained from the pathogenic bacterium Pseudomonas aeruginosagrown under various environmental conditions.