Spectral relative standard deviation: a practical benchmark in metabolomics
Spectral relative standard deviation: a practical benchmark in metabolomics
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DOI：
10.1039/b808986h
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发表时间：
2009-01-01
期刊：
影响因子：
4.2
通讯作者：
Viant, Mark R.
中科院分区：
文献类型：
--
作者：
Parsons, Helen M.;Ekman, Drew R.;Viant, Mark R.
根据定义，代谢组学数据集由大量代谢物的测量组成。技术（分析）和生物因素都会导致这些测量中的变化，而这些变化在所有代谢物中并不一致。因此，需要制定标准来评估来自所有检测到的代谢物的代谢组学数据集的可重复性。在这里，我们计算了10个代谢组学数据集的光谱范围内的相对标准偏差（rsd，也称为变异系数，CV），涵盖了哺乳动物、鱼类、无脊椎动物和细胞系等多种样本类型，并将其简洁地显示为箱线图。我们展示了光谱rsd在描述技术和个体间生物变异方面的多种应用：优化代谢物提取，比较分析技术，研究基质效应，比较单一和多个物种的生物流体和组织提取物，以优化实验设计。使用一维和二维NMR和质谱法记录的代谢组学数据集中的技术差异范围为1.6至20.6%（报告为中位光谱RSD）。个体间的生物变异通常较大，从实验室饲养的大鼠的组织提取物低至7.2%，到鱼血浆的58.4%。此外，对于一些数据集，我们确认光谱RSD值在不同的光谱处理方法（如基线校正、归一化和分节分辨率）中基本上是不变的。总之，我们建议光谱rsd及其中位数作为代谢组学研究的实用基准。
Metabolomics datasets, by definition, comprise of measurements of large numbers of metabolites. Both technical (analytical) and biological factors will induce variation within these measurements that is not consistent across all metabolites. Consequently, criteria are required to assess the reproducibility of metabolomics datasets that are derived from all the detected metabolites. Here we calculate spectrum-wide relative standard deviations (RSDs; also termed coefficient of variation, CV) for ten metabolomics datasets, spanning a variety of sample types from mammals, fish, invertebrates and a cell line, and display them succinctly as boxplots. We demonstrate multiple applications of spectral RSDs for characterising technical as well as inter-individual biological variation: for optimising metabolite extractions, comparing analytical techniques, investigating matrix effects, and comparing biofluids and tissue extracts from single and multiple species for optimising experimental design. Technical variation within metabolomics datasets, recorded using one- and two-dimensional NMR and mass spectrometry, ranges from 1.6 to 20.6% (reported as the median spectral RSD). Inter-individual biological variation is typically larger, ranging from as low as 7.2% for tissue extracts from laboratory-housed rats to 58.4% for fish plasma. In addition, for some of the datasets we confirm that the spectral RSD values are largely invariant across different spectral processing methods, such as baseline correction, normalisation and binning resolution. In conclusion, we propose spectral RSDs and their median values contained herein as practical benchmarks for metabolomics studies.