An R package to process LC/MS metabolomic data: MAIT(Metabolite Automatic Identification Toolkit)

Processing metabolomic liquid chromatography and mass spectrometry (LC/MS) data files is time consuming. Currently available R tools allow for only a limited number of processing steps and online tools are hard to use in a programmable fashion. This paper introduces the metabolite automatic identification toolkit MAIT package, which allows users to perform endto-end LC/MS metabolomic data analysis. The package is especially focused on improving the peak annotation stage and provides tools to validate the statistical results of the analysis. This validation stage consists of a repeated random sub-sampling cross-validation procedure evaluated through the classification ratio of the sample files. MAIT also includes functions that create a set of tables and plots, such as principal component analysis (PCA) score plots, cluster heat maps or boxplots. To identify which metabolites are related to statistically significant features, MAIT includes a metabolite database for a metabolite identification stage.