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Journal Articles Bioinformatics Year : 2019

ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra

Cécile Canlet
Patrick Tardivel
Rémi Servien

Abstract

Motivation: In metabolomics, the detection of new biomarkers from NMR spectra is a promising approach. However, this analysis remains difficult due to the lack of a whole workflow that handles spectra pre-processing, automatic identification and quantification of metabolites and statistical analyses, in a reproducible way. Results: We present ASICS, an R package that contains a complete workflow to analyse spectra from NMR experiments. It contains an automatic approach to identify and quantify metabolites in a complex mixture spectrum and uses the results of the quantification in untargeted and targeted statistical analyses. ASICS was shown to improve the precision of quantification in comparison to existing methods on two independent datasets. In addition, ASICS successfully recovered most metabolites that were found important to explain a two level condition describing the samples by a manual and expert analysis based on bucketing. It also found new relevant metabolites involved in metabolic pathways related to risk factors associated with the condition. Availability: ASICS is distributed as an R package, available on Bioconductor.
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Dates and versions

hal-02626125 , version 1 (26-05-2020)

Identifiers

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Gaëlle Lefort, Laurence Liaubet, Cécile Canlet, Patrick Tardivel, Marie-Christine Pere, et al.. ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra. Bioinformatics, 2019, 35 (21), pp.4356-4363. ⟨10.1093/bioinformatics/btz248⟩. ⟨hal-02626125⟩
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