Metabolomics provides a wealth of information about the biochemical status of cells, tissues, and other biological systems. However, for many researchers, processing the large quantities of data generated in typical metabolomics experiments poses a formidable challenge. Robust computational tools are required for all data processing steps, from handling raw data to high level statistical analysis and interpretation. This chapter describes several established methods for processing and analyzing metabolomics data within the R statistical programming environment. The focus is on processing LCMS data but the methods can be applied virtually to any analytical platform. We provide a step-by-step workflow to demonstrate how to integrate, analyze, and visualize LCMS-based metabolomics data using computational tools available in R. These concepts and methods will allow specialists and nonspecialists alike to develop and evaluate their own data more critically.
Part of the book: Metabolomics