Quantitative methods for metabolomic analyses evaluated in the Children's Health Exposure Analysis Resource (CHEAR).

ABSTRACT: With advances in technologies that facilitate metabolome-wide analyses, the incorporation of metabolomics in the pursuit of biomarkers of exposure and effect is rapidly evolving in population health studies. However, many analytic approaches are limited in their capacity to address high-dimensional metabolomics data within an epidemiologic framework, including the highly collinear nature of the metabolites and consideration of confounding variables. In this Children's Health Exposure Analysis Resource (CHEAR) network study, we showcase various analytic approaches that are established as well as novel in the field of metabolomics, including univariate single metabolite models, least absolute shrinkage and selection operator (LASSO), random forest, weighted quantile sum (WQS_RS) re

SUBMITTER: CHEAR Metabolomics Analysis Team 

PROVIDER: S-EPMC8041023 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature