This tutorial was held on March 15, 2021 and included an introduction to network analysis, with application to the analysis of metabolomics data. This workshop linked network visualizations with statistical analyses of high dimensional metabolomics data, introduced gaussian graphical models and methods for the detection of network subcomponents that link to health outcomes. Emphasis was placed on a suite of tools in R for network analyses of high dimensional data. Utility of these tools for ‘story telling’ in complex data settings was illustrated. Examples utilized metabolomics data from ongoing large-scale health research studies, although these techniques are transferrable across multiple domains. Please download tutorial material (data, R code, slides) from here: