Journal
BMC BIOINFORMATICS
Volume 11, Issue -, Pages -Publisher
BIOMED CENTRAL LTD
DOI: 10.1186/1471-2105-11-559
Keywords
-
Categories
Funding
- NIH [1P01ES016731-01, 2P30A1050409, 1UL1RR025008-01]
- University Research Committee of Emory University
Ask authors/readers for more resources
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/.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available