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pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra

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Title: pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra
Authors: Rodriguez-Martinez, A
Ayala, R
Posma, JM
Harvey, N
Jiménez, B
Sonomura, K
Sato, T-A
Matsuda, F
Zalloua, P
Gauguier, D
Nicholson, JK
Dumas, M-E
Item Type: Journal Article
Abstract: Motivation: Data processing is a key bottleneck for 1H NMR-based metabolic profiling of complex biological mixtures, such as biofluids. These spectra typically contain several thousands of signals, corresponding to possibly few hundreds of metabolites. A number of binning-based methods have been proposed to reduce the dimensionality of 1D 1H NMR datasets, including statistical recoupling of variables (SRV). Here, we introduce a new binning method, named JBA ("pJRES Binning Algorithm"), which aims to extend the applicability of SRV to pJRES spectra. Results: The performance of JBA is comprehensively evaluated using 617 plasma 1H NMR spectra from the FGENTCARD cohort. The results presented here show that JBA exhibits higher sensitivity than SRV to detect peaks from low-abundance metabolites. In addition, JBA allows a more efficient removal of spectral variables corresponding to pure electronic noise, and this has a positive impact on multivariate model building. Availability: The algorithm is implemented using the MWASTools R/Bioconductor package. Supplementary information: Supplementary data are available at Bioinformatics online.
Issue Date: 1-Jun-2019
Date of Acceptance: 22-Oct-2018
URI: http://hdl.handle.net/10044/1/64970
DOI: https://doi.org/10.1093/bioinformatics/bty837
ISSN: 1367-4803
Publisher: Oxford University Press (OUP)
Start Page: 1916
End Page: 1922
Journal / Book Title: Bioinformatics
Volume: 35
Issue: 11
Copyright Statement: © 2018 The Author(s). Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Sponsor/Funder: Medical Research Council (MRC)
Medical Research Council
Funder's Grant Number: MR/S004033/1
Keywords: Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Biochemical Research Methods
Biotechnology & Applied Microbiology
Computer Science, Interdisciplinary Applications
Mathematical & Computational Biology
Statistics & Probability
Biochemistry & Molecular Biology
Computer Science
01 Mathematical Sciences
06 Biological Sciences
08 Information and Computing Sciences
Publication Status: Published
Conference Place: England
Online Publication Date: 2018-10-23
Appears in Collections:School of Public Health