The metaRbolomics Toolbox in Bioconductor and beyond.
Metabolomics aims to measure and characterize the complex composition of metabolites in a biological system. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyze Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. This review by Steffen Neumann et al. provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. In total, this review summarizes more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub.
