A New Pipeline for the Normalization and Pooling of Metabolomics Data.

ABSTRACT: Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the ma

SUBMITTER: Viallon V 

PROVIDER: S-EPMC8467830 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature