Mixture model clustering for peak filtering in metabolomics

Rogers, S. , Daly, R. and Breitling, R. (2012) Mixture model clustering for peak filtering in metabolomics. In: WCSB2012 - 9th International Workshop on Computational Systems Biology, Ulm, Germany, 4-6 Jun 2012,

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Abstract

In recent years, the use of liquid chromatography coupled to mass spectrometry has enabled the high-throughput pro- filing of the metabolic composition of biological samples. However, the large amount of data obtained is often diffi- cult to analyse. This paper focuses on a particular problem, that of detecting and potentially removing derivative peaks of a substance of interest. A mixture model for clustering peaks based on chromatographic peak shape correlation is presented, and comparison of this model to the behaviour of a leading mass spectrometry analysis tool is presented. Based on the results, the mixture model is shown to have better overall performance characteristics.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Rogers, Dr Simon and Breitling, Professor Rainer and Daly, Dr Ronan
Authors: Rogers, S., Daly, R., and Breitling, R.
College/School:College of Medical Veterinary and Life Sciences > Institute of Molecular Cell and Systems Biology
College of Medical Veterinary and Life Sciences > School of Life Sciences
College of Science and Engineering > School of Computing Science

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