Maximum likelihood scaling (MALS)

descriptionPublicationkeyboard_double_arrow_right Article 01 Mar 2006 Netherlands English Publisher:WileyJournal:Journal of Chemometrics, volume 20, pages 120-127 (issn: 0886-9383, eissn: 1099-128X,

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Authors: Hoefsloot, H.C.J.; Verouden, M.P.H.; Westerhuis, J.A.; Smilde, A.K.;

doi: 10.1002/cem.996

handle: 11245/1.274555

Maximum likelihood scaling (MALS)

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Abstract

AbstractA filtering procedure is introduced for multivariate data that does not suffer from noise amplification by scaling. A maximum likelihood principal component analysis (MLPCA) step is used as a filter that partly removes noise. This filtering can be used prior to any subsequent scaling and multivariate analysis of the data and is especially useful for data with moderate and low signal‐to‐noise ratio's, such as metabolomics, proteomics and transcriptomics data. Copyright © 2007 John Wiley & Sons, Ltd.

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Netherlands

Related Organizations

Amsterdam UMC
Netherlands
University of Amsterdam
Netherlands

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