| Literature DB >> 28502011 |
Abstract
Metabolomics allows for the investigation of the small molecules found within living systems. Based on the design of the experiments, it is not uncommon for these analyses to include matrices of thousands of variables. In order to handle such large datasets, many have turned to multivariate statistical analyses to analyze and understand their data. Herein, we present protocols for using R to analyze metabolomic data using some of the more common multivariate statistical techniques.Keywords: Correlation network; Data analysis; Dendrograms; Metabolomics; PCA; Pheatmap; Qgraph; R programming language; Rgl
Mesh:
Year: 2017 PMID: 28502011 DOI: 10.1007/978-1-4939-6990-6_22
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745