Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/66034
Title: Semiautomated alignment of high-throughput metabolite profiles with chemometric tools
Authors: Wu, ZY
Zeng, ZD
Xiao, ZD
Mok, DKW
Liang, YZ
Chau, FT
Chan, HY
Issue Date: 2017
Publisher: Hindawi Publishing Corporation
Source: Journal of analytical methods in chemistry, 2017, v. 2017, 9402045 How to cite?
Journal: Journal of analytical methods in chemistry 
Abstract: The rapid increase in the use of metabolite profiling/fingerprinting techniques to resolve complicated issues in metabolomics has stimulated demand for data processing techniques, such as alignment, to extract detailed information. In this study, a new and automated method was developed to correct the retention time shift of high-dimensional and high-throughput data sets. Information from the target chromatographic profiles was used to determine the standard profile as a reference for alignment. A novel, piecewise data partition strategy was applied for the determination of the target components in the standard profile as markers for alignment. An automated target search (ATS) method was proposed to find the exact retention times of the selected targets in other profiles for alignment. The linear interpolation technique (LIT) was employed to align the profiles prior to pattern recognition, comprehensive comparison analysis, and other data processing steps. In total, 94 metabolite profiles of ginseng were studied, including the most volatile secondary metabolites. The method used in this article could be an essential step in the extraction of information from high-throughput data acquired in the study of systems biology, metabolomics, and biomarker discovery.
URI: http://hdl.handle.net/10397/66034
ISSN: 2090-8865
EISSN: 2090-8873
DOI: 10.1155/2017/9402045
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