MetaboAnalystR 2.0: From Raw Spectra to Biological Insights.
Jasmine ChongMai YamamotoJianguo XiaPublished in: Metabolites (2019)
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.
Keyphrases
- mass spectrometry
- liquid chromatography
- high resolution
- electronic health record
- high resolution mass spectrometry
- gas chromatography
- high performance liquid chromatography
- tandem mass spectrometry
- capillary electrophoresis
- big data
- simultaneous determination
- rna seq
- single cell
- optical coherence tomography
- high speed
- solid phase extraction
- data analysis
- psychometric properties
- deep learning
- ms ms
- solid state