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

Abstract : Motivation: Data processing is a key bottleneck for 1 H 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 1 D 1 H 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 1 H 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 and implementation: The algorithm is implemented using the MWASTools R/ Bioconductor package.
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https://hal-cnrs.archives-ouvertes.fr/hal-03089366
Contributor : Marc-Emmanuel Dumas Connect in order to contact the contributor
Submitted on : Monday, December 28, 2020 - 12:41:08 PM
Last modification on : Wednesday, October 20, 2021 - 12:17:17 AM
Long-term archiving on: : Monday, March 29, 2021 - 6:42:19 PM

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Andrea Rodriguez-Martinez, Rafael Ayala, Joram Posma, Nikita Harvey, Beatriz Jiménez, et al.. pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra. Bioinformatics, Oxford University Press (OUP), 2018, 35, pp.1916 - 1922. ⟨10.1093/bioinformatics/bty837⟩. ⟨hal-03089366⟩

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