Combined LC-MS/MS feature grouping, statistical prioritization, and interactive networking in msFeaST.

ABSTRACT:

Summary

Computational metabolomics workflows have revolutionized the untargeted metabolomics field. However, the organization and prioritization of metabolite features remains a laborious process. Organizing metabolomics data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets that also represent an intuitive and scientifically meaningful first stage of analysis in untargeted metabolomics. Exploiting such feature sets, feature-set testing has emerged as an approach that is widely used in genomics and targeted metabolomics pathway enrichment analyses. It allows for formally combining groupings with statistical testing into more meaningful pathway enrichment conclusions. Here, we present msFeaST (mass spectral Feature Set Testing), a

SUBMITTER: Mildau K 

PROVIDER: S-EPMC11471276 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature