Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric Tools
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 t...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Journal of Analytical Methods in Chemistry |
| Online Access: | http://dx.doi.org/10.1155/2017/9402045 |
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| author | Ze-ying Wu Zhong-da Zeng Zi-dan Xiao Daniel Kam-Wah Mok Yi-zeng Liang Foo-tim Chau Hoi-yan Chan |
| author_facet | Ze-ying Wu Zhong-da Zeng Zi-dan Xiao Daniel Kam-Wah Mok Yi-zeng Liang Foo-tim Chau Hoi-yan Chan |
| author_sort | Ze-ying Wu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-64eb5f61df9b413aa725aebe848753eb |
| institution | Kabale University |
| issn | 2090-8865 2090-8873 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Analytical Methods in Chemistry |
| spelling | doaj-art-64eb5f61df9b413aa725aebe848753eb2025-08-20T03:34:36ZengWileyJournal of Analytical Methods in Chemistry2090-88652090-88732017-01-01201710.1155/2017/94020459402045Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric ToolsZe-ying Wu0Zhong-da Zeng1Zi-dan Xiao2Daniel Kam-Wah Mok3Yi-zeng Liang4Foo-tim Chau5Hoi-yan Chan6School of Mathematics, Physics and Chemical Engineering, Changzhou Institute of Technology, Changzhou 213002, ChinaChemometrics and Herbal Medicine Laboratory, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongSchool of Chemical and Biological Engineering, Changsha University of Science & Technology, Changsha 410114, ChinaChemometrics and Herbal Medicine Laboratory, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongResearch Center of Modernization of Chinese Medicines, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, ChinaChemometrics and Herbal Medicine Laboratory, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongSchool of Chemical and Biological Engineering, Changsha University of Science & Technology, Changsha 410114, ChinaThe 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.http://dx.doi.org/10.1155/2017/9402045 |
| spellingShingle | Ze-ying Wu Zhong-da Zeng Zi-dan Xiao Daniel Kam-Wah Mok Yi-zeng Liang Foo-tim Chau Hoi-yan Chan Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric Tools Journal of Analytical Methods in Chemistry |
| title | Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric Tools |
| title_full | Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric Tools |
| title_fullStr | Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric Tools |
| title_full_unstemmed | Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric Tools |
| title_short | Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric Tools |
| title_sort | semiautomated alignment of high throughput metabolite profiles with chemometric tools |
| url | http://dx.doi.org/10.1155/2017/9402045 |
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