高等学校化学学报

高等学校化学学报 ›› 2011, Vol. 32 ›› Issue (12): 2769.

• 研究论文 • 上一篇    下一篇

素食人群尿液1H NMR代谢轮廓的多因素方差分析

董继扬1,2, 邓伶莉1, CHENG Kian-Kai2,3, GRIFFIN Julian L.2, 陈忠1   

  1. 1. 厦门大学电子科学系, 福建省等离子体与磁共振研究重点实验室, 厦门 361005;
    2. Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK;
    3. Department of Bioprocess Engineering, Universiti Teknologi Malaysia, Skudai 81310, Malaysia
  • 收稿日期:2010-12-07 修回日期:2011-01-28 出版日期:2011-12-10 发布日期:2011-11-25
  • 通讯作者: 陈忠 E-mail:chenz@xmu.edu.cn
  • 基金资助:

    国家自然科学基金(批准号: 11175149, 81171331)和中央高校基本科研业务费专项资金(批准号: 2011121046)资助.

Investigation of 1H NMR Profile of Vegetarian Human Urine Using ANOVA-based Multi-factor Analysis

DONG Ji-Yang1,2, DENG Ling-Li1, CHENG Kian-Kai2,3, GRIFFIN Julian L.2, CHEN Zhong1*   

  1. 1. Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen Universitty, Xiamen 361005, China;
    2. Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK;
    3. Department of Bioprocess Engineering, University of Technology Malaysia, Skudai 81310, Malaysia
  • Received:2010-12-07 Revised:2011-01-28 Online:2011-12-10 Published:2011-11-25
  • Contact: CHEN Zhong E-mail:chenz@xmu.edu.cn
  • Supported by:

    国家自然科学基金(批准号: 11175149, 81171331)和中央高校基本科研业务费专项资金(批准号: 2011121046)资助.

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摘要： 结合方差分析(ANOVA)和偏最小二乘法判别分析(PLS-DA)两种分析技术, 对素食和普食人群的尿液1H NMR谱进行分析. 利用ANOVA方法将数据矩阵分解为几个独立因素矩阵, 滤除干扰因素后, 再利用PLS-DA对单因素数据进行建模分析. 实验结果表明, ANOVA/PLS-DA方法可以有效地减少饮食因素和性别因素之间的相互影响, 使分析结果更具有生物学意义.

关键词: 多因素分析, 方差分析, 偏最小二乘法判别分析, 核磁共振代谢组学

Abstract: In this study, a technique that combined both analysis of variance(ANOVA) and partial least squares-discriminant analysis(PLS-DA) was used to compare the urine 1H NMR spectra of healthy people from a vegetarian and omnivorous population. In ANOVA/PLS-DA, the variation in data was first decomposed into different variance components that each contains a single source of variation. Each of the resulting variance components was then analyzed using PLS-DA. The experimental results showed that ANOVA/PLS-DA is efficient in disentangling the effect of diet and gender on the metabolic profile, and the method could be used to extract biologically relevant information for result interpretation.

Key words: Multi-factor analysis, Analysis of variance(ANOVA), Partial least squares-discriminant analysis(PLS-DA), NMR-based metabolomic

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