%0 Journal Article %T pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra %+ Department of surgery and cancer - Faculty of medecine %+ Kyoto University %+ Lebanese American University (LAU) %+ Immunologie et Cancérologie Intégratives (CRC - Inserm U1138) %+ Division of Computational and Systems Medicine, Imperial College London, London, SW7 2AZ, UK %+ Imperial College London - National Heart and Lung Institute %+ Centre National de la Recherche Scientifique (CNRS) %A Rodriguez-Martinez, Andrea %A Ayala, Rafael %A Posma, Joram, M %A Harvey, Nikita %A Jiménez, Beatriz %A Sonomura, Kazuhiro %A Sato, Taka-Aki %A Matsuda, Fumihiko %A Zalloua, Pierre %A Gauguier, Dominique %A Nicholson, Jeremy, K %A Dumas, Marc-Emmanuel %< avec comité de lecture %@ 1367-4803 %J Bioinformatics %I Oxford University Press (OUP) %V 35 %P 1916 - 1922 %8 2018-10-23 %D 2018 %R 10.1093/bioinformatics/bty837 %Z Life Sciences [q-bio]Journal articles %X 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. %G English %2 https://cnrs.hal.science/hal-03089366/document %2 https://cnrs.hal.science/hal-03089366/file/bty837-2.pdf %L hal-03089366 %U https://cnrs.hal.science/hal-03089366 %~ UNIV-PARIS5 %~ UNIV-PARIS7 %~ EPHE %~ CNRS %~ CORDELIERS %~ PSL %~ USPC %~ SORBONNE-UNIVERSITE %~ SORBONNE-UNIV %~ SU-SCIENCES %~ TEST-DEV %~ UNIV-PARIS %~ UP-SANTE %~ EPHE-PSL %~ SU-TI %~ ALLIANCE-SU