MetaboAnalystR 2.0: From Raw Spectra to Biological Insights

被引：270

作者：

Chong, Jasmine ^{[1
]}

Yamamoto, Mai ^{[1
]}

Xia, Jianguo ^{[1
,2
]}

机构：

[1] McGill Univ, Inst Parasitol, Montreal, PQ H3A 0G4, Canada

[2] McGill Univ, Dept Anim Sci, Montreal, PQ H3A 0G4, Canada

来源：

METABOLITES | 2019年 / 9卷 / 03期

基金：

加拿大自然科学与工程研究理事会;

关键词：

global metabolomics; LC-MS; spectra processing; pathway analysis; enrichment analysis; MASS-SPECTROMETRY DATA; METABOLOMICS; SOFTWARE; SERVER;

D O I：

10.3390/metabo9030057

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

070307 [化学生物学]; 071010 [生物化学与分子生物学];

摘要：

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.

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