ASICS: a new R package for identification and quantification of metabolites in complex 1D 1H NMR spectra - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Conference Poster Year : 2018

ASICS: a new R package for identification and quantification of metabolites in complex 1D 1H NMR spectra

Abstract

1H Nuclear Magnetic Resonance (NMR) is a high-throughput technology that allows to obtain metabolomic profile from easy-to-obtain fluids (such as blood) at moderate cost. It is thus a promising tool to detect practically usable biomarkers. However, its interpretation can be hard to make, because metabolites present from the 1H NMR spectrum of a complex mixture are not easily identified and quantified. To facilitate the use of such data, we developed a new R package, ASICS, that implements a method for automatic identification and quantification of metabolites in 1H NMR spectra. The package combines all the steps of the analysis (management of a reference library with pure metabolite spectra, preprocessing, quantification, diagnosis tools to assess the quality of the quantification, post-quantification statistical analyses). To assess the performance of ASICS, data from PORCINET (ANR-09-GENM-005) were used. Both the quantification and its impact on a post-quantification differential analysis were evaluated. First, correlations between ASICS relative quantifications and biochemical dosages of three metabolites were computed and a similar analysis was performed with other quantification methods like Autofit or batman. Second, a differential standard approach (based on a bucket analysis and a manual expert identification) was compared with the same analysis based on ASICS quantifications. These comparisons showed that ASICS allows for a faster and simpler direct biological interpretation than the classical bucket approach and obtains more precisely identified and quantified metabolites than other quantification methods. ASICS is released as a Bioconductor package and is also available as a GALAXY module.
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Dates and versions

hal-02789726 , version 1 (05-06-2020)

Identifiers

  • HAL Id : hal-02789726 , version 1
  • PRODINRA : 443616

Cite

Gaëlle Lefort, Laurence Liaubet, Cécile Canlet, Nathalie Vialaneix, Rémi Servien. ASICS: a new R package for identification and quantification of metabolites in complex 1D 1H NMR spectra. European Conference on Computational Biology (ECCB 2018), Sep 2018, Athènes, Greece. , 2018. ⟨hal-02789726⟩
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