MetaboAnalystR 2.0: From Raw Spectra to Biological Insights
MetaboAnalystR 2.0: From Raw Spectra to Biological Insights
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DOI：
10.3390/metabo9030057
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发表时间：
2019-03-22
期刊：
影响因子：
4.1
通讯作者：
Xia, Jianguo
中科院分区：
文献类型：
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作者：
Chong, Jasmine;Yamamoto, Mai;Xia, Jianguo
基于高分辨率液相色谱-质谱（LC-MS）的全球代谢组学在近年来的大规模多组学研究中得到越来越多的应用。这些复杂的代谢组学数据集的处理和解释已经成为当前计算代谢组学的一个关键挑战。在这里，我们介绍了MetaboAnalystR 2.0，用于全面的LC-MS数据处理，统计分析和功能解释。与之前的版本相比，这个新版本无缝集成了XCMS和CAMERA，以支持原始光谱处理和峰注释，并且还具有预测通路活动的mummichog和GSEA方法的高性能实现。使用合成基准数据集和临床数据集演示了MetaboAnalystR 2.0工作流的应用和效用。总之，MetaboAnalystR 2.0提供了一个统一而灵活的工作流程，可以在开源的R环境中对LC-MS代谢组学数据进行端到端分析。
Global metabolomics based on high-resolution liquid chromatography mass spectrometry (LC-MS) has been increasingly employed in recent large-scale multi-omics studies. Processing and interpretation of these complex metabolomics datasets have become a key challenge in current computational metabolomics. Here, we introduce MetaboAnalystR 2.0 for comprehensive LC-MS data processing, statistical analysis, and functional interpretation. Compared to the previous version, this new release seamlessly integrates XCMS and CAMERA to support raw spectral processing and peak annotation, and also features high-performance implementations of mummichog and GSEA approaches for predictions of pathway activities. The application and utility of the MetaboAnalystR 2.0 workflow were demonstrated using a synthetic benchmark dataset and a clinical dataset. In summary, MetaboAnalystR 2.0 offers a unified and flexible workflow that enables end-to-end analysis of LC-MS metabolomics data within the open-source R environment.