UNLABELLED: Current tools for liquid chromatography and mass spectrometry for metabolomic data cover a limited number of processing steps, whereas online tools are hard to use in a programmable fashion. This article introduces the Metabolite Automatic Identification Toolkit (MAIT) package, which makes it possible for users to perform metabolomic end-to-end liquid chromatography and mass spectrometry data analysis. MAIT is focused on improving the peak annotation stage and provides essential tools to validate statistical analysis results. MAIT generates output files with the statistical results, peak annotation and metabolite identification. AVAILABILITY AND IMPLEMENTATION: http://b2slab.upc.edu/software-and-downloads/metabolite-automatic-identification-toolkit/.

UNLABELLED: Liquid chromatography coupled to mass spectrometry (LC/MS) has become widely used in Metabolomics. Several artefacts have been identified during the acquisition step in large LC/MS metabolomics experiments, including ion suppression, carryover or changes in the sensitivity and intensity. Several sources have been pointed out as responsible for these effects. In this context, the drift effects of the peak intensity is one of the most frequent and may even constitute the main source of variance in the data, resulting in misleading statistical results when the samples are analysed. In this article, we propose the introduction of a methodology based on a common variance analysis before the data normalization to address this issue. This methodology was tested and compared with four other methods by calculating the Dunn and Silhouette indices of the quality control classes. The results showed that our proposed methodology performed better than any of the other four methods. As far as we know, this is the first time that this kind of approach has been applied in the metabolomics context. AVAILABILITY AND IMPLEMENTATION: The source code of the methods is available as the R package intCor at http://b2slab.upc.edu/software-and-downloads/intensity-drift-correction/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.