Statistical significance analysis of nuclear magnetic resonance-based metabonomics data
Statistical significance analysis of nuclear magnetic resonance-based metabonomics data
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DOI：
10.1016/j.ab.2010.02.005
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发表时间：
2010-06-01
影响因子：
2.9
通讯作者：
Kennedy, Michael A.
中科院分区：
文献类型：
--
作者：
Goodpaster, Aaron M.;Romick-Rosendale, Lindsey E.;Kennedy, Michael A.
使用基于核磁共振 (NMR) 的代谢组学来寻找人类疾病生物标志物正变得越来越普遍。对于许多研究人员来说，最终目标是将生物标志物发现转化为临床应用。研究通常涉及来自不同教育和培训背景的研究人员，包括医生、学术研究人员和临床工作人员。在评估潜在的生物标志物时，临床医生通常使用统计显着性测试语言，而院士通常使用不执行统计显着性评估的多元统计分析技术。在本文中，我们概述了一种将统计显着性检验与传统主成分分析数据表示相结合的方法。引入决策树算法来选择适当的统计测试并将其应用于载荷图数据，然后根据 P 分数对热图进行颜色编码，从而能够直接直观地评估统计显着性。必须应用多重比较校正来确定 P 分数，从中可以做出可靠的推论。了解统计显着性桶的平均值和标准差可以计算给定统计功效的效应大小和研究规模。使用先前研究的数据证明了方法。综合代谢组学数据评估方法应有助于将基于核磁共振的人类疾病生物标志物代谢组学发现转化为临床应用。 (C) 2010 Elsevier Inc. 保留所有权利。
Use of nuclear magnetic resonance (NMR)-based metabonomics to search for human disease biomarkers is becoming increasingly common. For many researchers, the ultimate goal is translation from biomarker discovery to clinical application. Studies typically involve investigators from diverse educational and training backgrounds, including physicians, academic researchers, and clinical staff. In evaluating potential biomarkers, clinicians routinely use statistical significance testing language, whereas academicians typically use multivariate statistical analysis techniques that do not perform statistical significance evaluation. In this article, we outline an approach to integrate statistical significance testing with conventional principal components analysis data representation. A decision tree algorithm is introduced to select and apply appropriate statistical tests to loadings plot data, which are then heat map color-coded according to P score, enabling direct visual assessment of statistical significance. A multiple comparisons correction must be applied to determine P scores from which reliable inferences can be made. Knowledge of means and standard deviations of statistically significant buckets enabled computation of effect sizes and study sizes for a given statistical power. Methods were demonstrated using data from a previous study. Integrated metabonomics data assessment methodology should facilitate translation of NMR-based metabonomics discovery of human disease biomarkers to clinical use. (C) 2010 Elsevier Inc. All rights reserved.