The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC-TOF MS metabolome samples

Metabolomics by gas chromatography/mass spectrometry (GC/MS) provides a standardized and reliable platform for understanding small molecule biology. Since 2005, the West Coast Metabolomics Center at the University of California at Davis has collated GC/MS metabolomics data from over 156,000 samples and 2000 studies into the standardized BinBase database. We believe that the observations from these samples will provide meaningful insight to biologists and that our data treatment and webtool will provide insight to others who seek to standardize disparate metabolomics studies. We here developed an easy-to-use query interface, BinDiscover, to enable intuitive, rapid hypothesis generation for biologists based on these metabolomic samples. BinDiscover creates observation summaries and graphics across a broad range of species, organs, diseases, and compounds. Throughout the components of BinDiscover, we emphasize the use of ontologies to aggregate large groups of samples based on the proximity of their metadata within these ontologies. This adjacency allows for the simultaneous exploration of entire categories such as rodents, digestive tract, or amino acids. The ontologies are particularly relevant for BinDiscover's ontologically grouped differential analysis, which, like other components of BinDiscover, creates clear graphs and summary statistics across compounds and biological metadata. We exemplify BinDiscover's extensive applicability in three showcases across biological domains.

Automated summary

Metabolomics by GC/MS is a standardized and reliable platform for understanding small molecule biology. The West Coast Metabolomics Center at UC Davis has collated over 156,000 samples and 2000 studies into the BinBase database, which provides meaningful insight to biologists and helps standardize metabolomics studies. They have developed an easy-to-use query interface, BinDiscover, for intuitive hypothesis generation based on these metabolomic samples.