Improved analysis of multivariate data by variable stability scaling: application to NMR-based metabolic profiling
Improved analysis of multivariate data by variable stability scaling: application to NMR-based metabolic profiling
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DOI：
10.1016/s0003-2670(03)00094-1
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发表时间：
2003-08-25
影响因子：
6.2
通讯作者：
Nicholson, JK
中科院分区：
文献类型：
--
作者：
Keun, HC;Ebbels, TMD;Nicholson, JK
变量标度改变了数据的协方差结构，影响了多变量分析和校准的结果。本文提出了一种新的方法——变稳定性（VAST）标度法，它根据每个变量的稳定性度量来对其进行加权。在动物模型中，作为单侧肾切除术代谢组学研究的一部分，尿液的H-1核磁共振光谱数据集证明了VAST标度的有益作用。VAST标度的应用提高了偏最小二乘判别分析（PLS-DA）模型的分类能力和预测能力。此外，还对正交信号校正（OSC）等其他数据缩放和预处理方法的效果进行了测试。在类别预测方面，VAST缩放产生了最稳健的模型，在这方面优于OSC。因此，尽管存在由正常生理变化引起的更大的生物学差异，但单侧肾切除术引起的微妙但一致的代谢扰动可以准确地表征。VAST扩展是一种可解释的、健壮的、易于实现的数据处理，用于增强多变量数据分析。(C) 2003 Elsevier Science B.V.版权所有
Variable scaling alters the covariance structure of data, affecting the outcome of multivariate analysis and calibration. Here we present a new method, variable stability (VAST) scaling, which weights each variable according to a metric of its stability. The beneficial effect of VAST scaling is demonstrated for a data set of H-1 NMR spectra of urine acquired as part of a metabonomic study into the effects of unilateral nephrectomy in an animal model. The application of VAST scaling improved the class distinction and predictive power of partial least squares discriminant analysis (PLS-DA) models. The effects of other data scaling and pre-processing methods, such as orthogonal signal correction (OSC), were also tested. VAST scaling produced the most robust models in terms of class prediction, outperforming OSC in this aspect. As a result the subtle, but consistent, metabolic perturbation caused by unilateral nephrectomy could be accurately characterised despite the presence of much greater biological differences caused by normal physiological variation. VAST scaling presents itself as an interpretable, robust and easily implemented data treatment for the enhancement of multivariate data analysis. (C) 2003 Elsevier Science B.V. All rights reserved.