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, Jiyang, Kian, Kai Cheng, Xu, Jingjing, Chen, Zhong, Griffin, Julian L.
Format: Article
Published: Elsevier BV 2011
Subjects:
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author Dong, Jiyang
Kian, Kai Cheng
Xu, Jingjing
Chen, Zhong
Griffin, Julian L.
author_facet Dong, Jiyang
Kian, Kai Cheng
Xu, Jingjing
Chen, Zhong
Griffin, Julian L.
author_sort Dong, Jiyang
collection ePrints
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.
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spelling utm.eprints-449562020-10-13T01:29:31Z http://eprints.utm.my/44956/ Group aggregating normalization method for the preprocessing of NMR-based metabolomic data Dong, Jiyang Kian, Kai Cheng Xu, Jingjing Chen, Zhong Griffin, Julian L. QH Natural history 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 BV 2011 Article PeerReviewed Dong, Jiyang and Kian, Kai Cheng and Xu, Jingjing and Chen, Zhong and Griffin, Julian 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
spellingShingle QH Natural history
Dong, Jiyang
Kian, Kai Cheng
Xu, Jingjing
Chen, Zhong
Griffin, Julian L.
Group aggregating normalization method for the preprocessing of NMR-based metabolomic data
title 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_short 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
topic QH Natural history
work_keys_str_mv AT dongjiyang groupaggregatingnormalizationmethodforthepreprocessingofnmrbasedmetabolomicdata
AT kiankaicheng groupaggregatingnormalizationmethodforthepreprocessingofnmrbasedmetabolomicdata
AT xujingjing groupaggregatingnormalizationmethodforthepreprocessingofnmrbasedmetabolomicdata
AT chenzhong groupaggregatingnormalizationmethodforthepreprocessingofnmrbasedmetabolomicdata
AT griffinjulianl groupaggregatingnormalizationmethodforthepreprocessingofnmrbasedmetabolomicdata