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The method for metabonomics data analysis applied on the urine of the rats administered with Liu Wei Di Huang Pills

机译:代谢组学数据分析方法在六味地黄丸给药大鼠尿液中的应用

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Data sets from metabonomics or metabolic profiling experiments are becoming increasingly complex, which are hard to summarize and visualize without appropriate tools. The use of chemometric tools, such as orthogonal signal correction (OSC), principal component analysis (PCA), partial least squares to latent structure discriminant analysis (PLS-DA), and OSC-PLS-DA make the data dimensionality reduction and interpretation much easier. Here we showed a system method based on PCA, OSC-PLS-DA for metabonomic data analysis; Furthermore, the loading plots of mass data were used for the biomarkers discovery. As an example, dataset from Liu Wei Di Huang Pills administrated rats urine collected by LC/MS/MS was used to demonstrate this method. The results indicate that PCA combined with OSC-PLS-DA was a time-saving tool for data interpretation and biomarkers discovery.
机译:来自代谢组学或代谢谱分析实验的数据集变得越来越复杂,如果没有合适的工具很难对其进行汇总和可视化。使用化学计量工具,例如正交信号校正(OSC),主成分分析(PCA),隐结构判别分析的偏最小二乘(PLS-DA)和OSC-PLS-DA,可以大大减少数据的维数和解释更轻松。在这里,我们展示了一种基于PCA,OSC-PLS-DA的系统代谢组学数据分析方法;此外,将大量数据的加载图用于生物标记物发现。例如,使用LC / MS / MS收集的六味地黄丸给药大鼠尿液数据集来证明该方法。结果表明,PCA与OSC-PLS-DA结合使用是一种节省时间的数据解释和生物标记物发现工具。

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