作者: Gaëlle Lefort , Laurence Liaubet , Cécile Canlet , Patrick Tardivel , Marie-Christine Père
DOI: 10.1093/BIOINFORMATICS/BTZ248
关键词: Identification (information) 、 Workflow 、 Metabolomics 、 Bioconductor 、 Computer science 、 Data mining 、 Biomarker (medicine) 、 Metabolic pathway 、 Proton NMR 、 R package
摘要: Motivation In metabolomics, the detection of new biomarkers from Nuclear Magnetic Resonance (NMR) spectra is a promising approach. However, this analysis remains difficult due to lack whole workflow that handles pre-processing, automatic identification and quantification metabolites statistical analyses, in reproducible way. Results We present ASICS, an R package contains complete analyse NMR experiments. It approach identify quantify complex mixture spectrum uses results untargeted targeted analyses. ASICS was shown improve precision comparison existing methods on two independent datasets. addition, successfully recovered most were found important explain level condition describing samples by manual expert based bucketing. also relevant involved metabolic pathways related risk factors associated with condition. Availability implementation distributed as package, available Bioconductor. Supplementary information data are at Bioinformatics online.