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Group aggregating normalization method for the preprocessing of NMR-based metabolomic data

Data normalization plays a crucial role in metabolomics to take into account the inevitable variation in sample concentration and the efficiency of sample preparation procedure. The conventional methods such as constant sum normalization (CSN) and probabilistic quotient normalization (PQN) are widel...

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Main Authors:	Dong, J., Cheng, Kian Kai, Xu, J., Chen, Z., Griffin, J. L.
Format:	Article
Published:	Elsevier B.V. 2011
Subjects:	QD Chemistry
Online Access:	http://eprints.utm.my/id/eprint/29150/ http://dx.doi.org/10.1016/j.chemolab.2011.06.002
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id	my.utm.29150
record_format	eprints
spelling	my.utm.291502020-10-22T04:04:14Z http://eprints.utm.my/id/eprint/29150/ Group aggregating normalization method for the preprocessing of NMR-based metabolomic data Dong, J. Cheng, Kian Kai Xu, J. Chen, Z. Griffin, J. L. QD Chemistry Data normalization plays a crucial role in metabolomics to take into account the inevitable variation in sample concentration and the efficiency of sample preparation procedure. The conventional methods such as constant sum normalization (CSN) and probabilistic quotient normalization (PQN) are widely used, but both methods have their own shortcomings. In the current study, a new data normalization method called group aggregating normalization (GAN) is proposed, by which the samples were normalized so that they aggregate close to their group centers in a principal component analysis (PCA) subspace. This is in contrast with CSN and PQN which rely on a constant reference for all samples. The evaluation of GAN method using both simulated and experimental metabolomic data demonstrated that GAN produces more robust model in the subsequent multivariate data analysis, more superior than both CSN and PQN methods. The current study also demonstrated that some of the differential metabolites identified using the CSN or PQN method could be false positives due to improper data normalization. Elsevier B.V. 2011-10-15 Article PeerReviewed Dong, J. and Cheng, Kian Kai and Xu, J. and Chen, Z. and Griffin, J. L. (2011) Group aggregating normalization method for the preprocessing of NMR-based metabolomic data. Chemometrics and Intelligent Laboratory Systems, 108 (2). pp. 123-132. ISSN 0169-7439 http://dx.doi.org/10.1016/j.chemolab.2011.06.002 DOI:10.1016/j.chemolab.2011.06.002
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	QD Chemistry
spellingShingle	QD Chemistry Dong, J. Cheng, Kian Kai Xu, J. Chen, Z. Griffin, J. L. Group aggregating normalization method for the preprocessing of NMR-based metabolomic data
description	Data normalization plays a crucial role in metabolomics to take into account the inevitable variation in sample concentration and the efficiency of sample preparation procedure. The conventional methods such as constant sum normalization (CSN) and probabilistic quotient normalization (PQN) are widely used, but both methods have their own shortcomings. In the current study, a new data normalization method called group aggregating normalization (GAN) is proposed, by which the samples were normalized so that they aggregate close to their group centers in a principal component analysis (PCA) subspace. This is in contrast with CSN and PQN which rely on a constant reference for all samples. The evaluation of GAN method using both simulated and experimental metabolomic data demonstrated that GAN produces more robust model in the subsequent multivariate data analysis, more superior than both CSN and PQN methods. The current study also demonstrated that some of the differential metabolites identified using the CSN or PQN method could be false positives due to improper data normalization.
format	Article
author	Dong, J. Cheng, Kian Kai Xu, J. Chen, Z. Griffin, J. L.
author_facet	Dong, J. Cheng, Kian Kai Xu, J. Chen, Z. Griffin, J. L.
author_sort	Dong, J.
title	Group aggregating normalization method for the preprocessing of NMR-based metabolomic data
title_short	Group aggregating normalization method for the preprocessing of NMR-based metabolomic data
title_full	Group aggregating normalization method for the preprocessing of NMR-based metabolomic data
title_fullStr	Group aggregating normalization method for the preprocessing of NMR-based metabolomic data
title_full_unstemmed	Group aggregating normalization method for the preprocessing of NMR-based metabolomic data
title_sort	group aggregating normalization method for the preprocessing of nmr-based metabolomic data
publisher	Elsevier B.V.
publishDate	2011
url	http://eprints.utm.my/id/eprint/29150/ http://dx.doi.org/10.1016/j.chemolab.2011.06.002
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score	13.211869

Group aggregating normalization method for the preprocessing of NMR-based metabolomic data

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