From Data Processing to Multivariate Validation - Essential Steps in Extracting Interpretable Information from Metabolomics Data

Author(s): Mattias Eliasson, Stefan Rannar, Johan Trygg

Journal Name: Current Pharmaceutical Biotechnology

Volume 12 , Issue 7 , 2011

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In metabolomics studies there is a clear increase of data. This indicates the necessity of both having a battery of suitable analysis methods and validation procedures able to handle large amounts of data. In this review, an overview of the metabolomics data processing pipeline is presented. A selection of recently developed and most cited data processing methods is discussed. In addition, commonly used chemometric and machine learning analysis methods as well as validation approaches are described.

Keywords: Multivariate data analysis, data processing, chemometrics, metabolomics, statistical validation, validation procedures, chemometric and machine learning analysis, NMR, downstream data analysis, Filtration, non-linear regression method

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Article Details

Year: 2011
Page: [996 - 1004]
Pages: 9
DOI: 10.2174/138920111795909041
Price: $65

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PDF: 15