PAIRUP-MS: Pathway analysis and imputation to relate unknowns in profiles from mass spectrometry-based metabolite data.

ABSTRACT: Metabolomics is a powerful approach for discovering biomarkers and for characterizing the biochemical consequences of genetic variation. While untargeted metabolite profiling can measure thousands of signals in a single experiment, many biologically meaningful signals cannot be readily identified as known metabolites nor compared across datasets, making it difficult to infer biology and to conduct well-powered meta-analyses across studies. To overcome these challenges, we developed a suite of computational methods, PAIRUP-MS, to match metabolite signals across mass spectrometry-based profiling datasets and to generate metabolic pathway annotations for these signals. To pair up signals measured in different datasets, where retention times (RT) are often not comparable or even available, we

SUBMITTER: Hsu YH 

PROVIDER: S-EPMC6347288 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature