Instructor: Dr. Oliver Fiehn, UC Davis
Required software: None
Participant prerequisites: None
Short description of the course: Epidemiologists increasingly use metabolomic data in large human cohort studies that focus on public health problems and risk factor analyses. Classically, only a few variables were used in epidemiological analyses which were then stratified by multiple adjustments to find robust associations with phenotypes. Now, GWAS analyses have led the way for metabolite-wide association studies. How robust are metabolite data? What are the best normalization strategies? How should we deal with missing data, QC pools, and blanks? How can different studies be combined to increase power? Which identifiers could be used, and what is good coverage for metabolomic studies? These questions will be discussed in this short course to provide an overview of metabolomics including realistic goals and considerations for study designs, and metabolite coverage from commercial providers versus core facilities.