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      Proposed minimum reporting standards for chemical analysis : Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI)

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          Abstract

          There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msi-workgroups-feedback@lists.sourceforge.net. Further, community input related to this document can also be provided via this electronic forum.

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          Potential of metabolomics as a functional genomics tool.

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            Proposed minimum reporting standards for data analysis in metabolomics

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              A proposed framework for the description of plant metabolomics experiments and their results.

              The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.
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                Author and article information

                Journal
                Metabolomics
                Metabolomics
                Springer Science and Business Media LLC
                1573-3882
                1573-3890
                September 19 2007
                September 12 2007
                September 19 2007
                : 3
                : 3
                : 211-221
                Article
                10.1007/s11306-007-0082-2
                3772505
                24039616
                c40e35f7-6b7a-40b3-9e5d-3f55aa028840
                © 2007

                http://www.springer.com/tdm

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