Chemometric methods in data processing of mass spectrometry-based metabolomics: A review

被引:223
|
作者
Yi, Lunzhao [1 ]
Dong, Naiping [3 ]
Yun, Yonghuan [2 ]
Deng, Baichuan [4 ]
Ren, Dabing [1 ]
Liu, Shao [5 ]
Liang, Yizeng [2 ]
机构
[1] Kunming Univ Sci & Technol, Yunnan Food Safety Res Inst, Kunming 650500, Peoples R China
[2] Cent South Univ, Coll Chem & Chem Engn, Changsha 410083, Hunan, Peoples R China
[3] Hong Kong Polytech Univ, Dept Appl Biol & Chem Technol, Hong Kong 999077, Hong Kong, Peoples R China
[4] South China Agr Univ, Coll Anim Sci, Guangzhou 510642, Guangdong, Peoples R China
[5] Cent South Univ, Xiangya Hosp, Changsha 410008, Hunan, Peoples R China
关键词
Metabolomics; Chemometrics; Biomarker; Identification of metabolites; Data preprocessing; Modeling; PARTIAL LEAST-SQUARES; ISOTOPIC ABUNDANCE MEASUREMENTS; MULTIVARIATE CURVE RESOLUTION; RETENTION TIME ALIGNMENT; GAS-CHROMATOGRAPHY; LC-MS; METABOLITE IDENTIFICATION; PEAK DETECTION; ACCURATE MASS; VARIABLE SELECTION;
D O I
10.1016/j.aca.2016.02.001
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
This review focuses on recent and potential advances in chemometric methods in relation to data processing in metabolomics, especially for data generated from mass spectrometric techniques. Metabolomics is gradually being regarded a valuable and promising biotechnology rather than an ambitious advancement. Herein, we outline significant developments in metabolomics, especially in the combination with modern chemical analysis techniques, and dedicated statistical, and chemometric data analytical strategies. Advanced skills in the preprocessing of raw data, identification of metabolites, variable selection, and modeling are illustrated. We believe that insights from these developments will help narrow the gap between the original dataset and current biological knowledge. We also discuss the limitations and perspectives of extracting information from high-throughput datasets. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:17 / 34
页数:18
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