An anchored experimental design and meta-analysis approach to address batch effects in large-scale metabolomics.

ABSTRACT: Untargeted metabolomics studies are unbiased but identifying the same feature across studies is complicated by environmental variation, batch effects, and instrument variability. Ideally, several studies that assay the same set of metabolic features would be used to select recurring features to pursue for identification. Here, we developed an anchored experimental design. This generalizable approach enabled us to integrate three genetic studies consisting of 14 test strains of Caenorhabditis elegans prior to the compound identification process. An anchor strain, PD1074, was included in every sample collection, resulting in a large set of biological replicates of a genetically identical strain that anchored each study. This enables us to estimate treatment effects within each

SUBMITTER: Shaver AO 

PROVIDER: S-EPMC9682135 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature