Pathway analysis in metabolomics: Recommendations for the use of over-representation analysis.

ABSTRACT: Over-representation analysis (ORA) is one of the commonest pathway analysis approaches used for the functional interpretation of metabolomics datasets. Despite the widespread use of ORA in metabolomics, the community lacks guidelines detailing its best-practice use. Many factors have a pronounced impact on the results, but to date their effects have received little systematic attention. Using five publicly available datasets, we demonstrated that changes in parameters such as the background set, differential metabolite selection methods, and pathway database used can result in profoundly different ORA results. The use of a non-assay-specific background set, for example, resulted in large numbers of false-positive pathways. Pathway database choice, evaluated using three of the most popular

SUBMITTER: Wieder C 

PROVIDER: S-EPMC8448349 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature