ASICS: a new R package for identification and quantification of metabolites in complex 1H NMR spectra
Résumé
1H Nuclear Magnetic Resonance (NMR) is a high-throughput technology that allows to obtain metabolomic profile from easy-to-obtain fluids at moderate cost. It is a promising tool to detect practically usable biomarkers. However, its interpretation can be hard to make, because metabolites present from the spectrum of a complex mixture are often identified and quantified only from expert knowledge. To facilitate the use of such data, we developed a new R package, ASICS, that implements a method for the automatic identification and quantification of metabolites in 1H NMR spectra. The package combines all the steps of the analysis (management of a reference library, preprocessing, quantification, diagnosis tools to assess the quality of the quantification, post-quantification statistical analyses). To assess the performance of ASICS, both the quantification and its impact on a post-quantification differential analysis were evaluated. Correlations between ASICS relative quantifications and biochemical dosages were computed and a similar analysis was performed with other quantification methods. 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 an R/Bioconductor package.