Yunnan Food Safety Research Institute, Kunming University of Science and Technology, Kunming, 650500, China.
Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, 999077, China.
Anal Chim Acta. 2016 Mar 31;914:17-34. doi: 10.1016/j.aca.2016.02.001. Epub 2016 Feb 16.
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.
本文重点关注了近年来化学计量学方法在代谢组学数据处理方面的最新进展和潜在应用，特别是针对质谱技术所产生的数据。代谢组学正逐渐被视为一种有价值且有前景的生物技术，而不仅仅是一种雄心勃勃的技术进步。本文概述了代谢组学的重要发展，特别是与现代化学分析技术相结合的发展，以及专用的统计和化学计量学数据分析策略。文中还介绍了原始数据的预处理、代谢物鉴定、变量选择和建模等高级技术。我们相信，这些进展将有助于缩小原始数据集与当前生物学知识之间的差距。我们还讨论了从高通量数据集提取信息的局限性和展望。
