IDSL.CCDB: a database for exploring inter-chemical correlations in metabolomics and exposomics datasets
Inter-chemical correlations in metabolomics and exposomics datasets provide valuable information for studying relationships among reported chemicals measured in human specimens. With an increase in the size of these datasets, a network graph analysis and visualization of the correlation structure is difficult to interpret. While co-regulatory genes databases have been developed, a similar database for metabolites and chemicals have not been developed yet. We have developed the Integrated Data Science Laboratory for Metabolomics and Exposomics - Chemical Correlation Database (IDSL.CCDB), as a systematic catalogue of inter-chemical correlation in publicly available metabolomics and exposomics studies. The database has been provided via an online interface to create single compound-centric views that are clear, readable and meaningful. We have demonstrated various applications of the database to explore: 1) the chemicals from a chemical class such as Per- and Polyfluoroalkyl Substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), phthalates and tobacco smoke related metabolites; 2) xenobiotic metabolites such as caffeine and acetaminophen; 3) endogenous metabolites (acyl-carnitines); and 4) unannotated peaks for PFAS. The database has a rich collection of 36 human studies, including the National Health and Nutrition Examination Survey (NHANES) and high-quality untargeted metabolomics datasets. IDSL.CCDB is supported by a simple, interactive and user-friendly web-interface to retrieve and visualize the inter-chemical correlation data. The IDSL.CCDB has the potential to be a key computational resource in metabolomics and exposomics facilitating the expansion of our understanding about biological and chemical relationships among metabolites and chemical exposures in the human body. The database is available at www.ccdb.idsl.me site.