An integrated computational platform for metabolomics data analysis

Abstract

The field of metabolomics, one of the omics technologies that have recently revolutionized biological research, provides multiple challenges for data analysis, that have been addressed by several computational tools. However, none addresses the multiplicity of existing techniques and data analysis tasks. Here, we propose a novel R package that provides a set of functions for metabolomics data analysis, including data loading in different formats, pre-processing, univariate and multivariate data analysis, machine learning and feature selection. The package supports the analysis of data from the main experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment, promoting the rapid development and sharing of data analysis pipelines.