Automated metabolite formula ranking using formula subset analysis for LC-MS/MS-based metabolomics.

ABSTRACT:

Introduction

Metabolite identification remains a bottleneck in untargeted liquid chromatography-tandem mass spectrometry (LC-MS) metabolomics studies, particularly when the underlying metabolite is absent in the tandem mass spectrometry (MS/MS) databases.

Objective

A new approach, formula subset analysis (FSA), was developed to effectively prescreen and rank the chemical formula candidates for an MS/MS spectrum.

Methods

This approach first computes mother-daughter relationships (MDRs) among possible formulas of fragments and the precursor under a given mass tolerance and then determines the characteristic fragments (CFs) that only present one MDR with the precursor and other fragments. Subsequently, the precursor formula candidates are ranked by the scores derived fro

SUBMITTER: Lynn KS 

PROVIDER: S-EPMC12669256 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature