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2010

Quantification and deconvolution of asymmetric LC-MS peaks using the bi-Gaussian mixture model and statistical model selection

11 years 5 months ago
Quantification and deconvolution of asymmetric LC-MS peaks using the bi-Gaussian mixture model and statistical model selection
Background: Liquid chromatography-mass spectrometry (LC-MS) is one of the major techniques for the quantification of metabolites in complex biological samples. Peak modeling is one of the key components in LC-MS data pre-processing. Results: To quantify asymmetric peaks with high noise level, we developed an estimation procedure using the bi-Gaussian function. In addition, to accurately quantify partially overlapping peaks, we developed a deconvolution method using the bi-Gaussian mixture model combined with statistical model selection. Conclusions: Using extensive simulations and real data, we demonstrated the advantage of the bi-Gaussian mixture model over the Gaussian mixture model and the method of kernel smoothing combined with signal summation in peak quantification and deconvolution. The method is implemented in the R package apLCMS: http://www.sph.emory.edu/apLCMS/. Background Liquid chromatography-mass spectrometry (LC-MS) is one of the major techniques in metabolomics [1-4],...
Tianwei Yu, Hesen Peng
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2010
Where BMCBI
Authors Tianwei Yu, Hesen Peng
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