Proposed minimum reporting standards for data analysis in metabolomics

By Royston Goodacre, David Broadhurst, Age K. Smilde, Bruce S. Kristal, J. Baker, R. Beger, C. Bessant, S. Connor, G. Capuani, A. Craig and 9 more. Metabolomics, 2007

435 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c93bca8d9ec1c95b290c7a72ab4420990ef83f56

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Citations in the corpus

Survey of the Quality of Experimental Design, Statistical Analysis and Reporting of Research Using Animals (2009, background): “Reporting guidelines have also been developed for other specific research areas [28–33].”
Proposed minimum reporting standards for chemical analysis (2007, background): “Further, the issue of sample collection and processing is being addressed by multiple MSI working groups and thus, there is some overlap on this theme (Fiehn et al. 2007; Griffin et al. 2007; van der Werf et al. 2007).”
MetaboLights—an open-access general-purpose repository for metabolomics studies and associated meta-data (2012, methodology): “MSI developed checklists and standards that have subsequently been adopted by the community, including minimum metadata reporting recommendations (24).”
Computational mass spectrometry for small molecules (2013, background): “The Data Analysis Working Group (DAWG) [60] as part of the MSI proposed reporting standards for metabolomics studies that include a reporting vocabulary and will help reproducing these studies and drawing conclusions from the resulting data.”
Multivariate Analysis in Metabolomics. (2012, methodology): “A summarization of the procedures involved for preprocessing of metabolic fingerprinting datasets has been well described, and efforts have been made to standardize the processes [54, 55].”
Quality control for plant metabolomics: reporting MSI-compliant studies. (2008, methodology): “The Metabolomics Standards Initiative has released minimum requirements for reporting data transformations and statistics (Goodacre et al., 2007).”
A tutorial review: Metabolomics and partial least squares-discriminant analysis--a marriage of convenience or a shotgun wedding. (2015, methodology): “This subject has been repeatedly reported in the literature [14,21–24,68,69] with classification difficulties in metabolomic analyses being mainly a result of high data dimensionality, where the generated data contains many variables and insufficient number of samples.”
A primer to nutritional metabolomics by NMR spectroscopy and chemometrics (2013, background): “Spectral processing of single NMR spectra will not be considered here, but the quality of the spectra and thus the quantitative information in the spectra will depend on the quality and homogeneity of the external magnetic field (shimming) and on precise and accurate tuning and matching of the nucle”