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Front Bioeng Biotechnol. 2014 Dec 16;2:72. doi: 10.3389/fbioe.2014.00072. eCollection 2014.

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

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Research and Innovation Centre, Fondazione E. Mach , San Michele all'Adige, Trento , Italy.
Research and Innovation Centre, Fondazione E. Mach , San Michele all'Adige, Trento , Italy ; Institute of Plant Sciences, Faculty of Agriculture, The Hebrew University of Jerusalem , Rehovot , Israel.


Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.


GC-MS; ISA-Tab; LC-MS; data analysis; metabolomics; pipeline

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