MetaboList

MetaboList annotates metabolites from high-resolution data-independent acquisition (DIA) mass spectrometry by providing computational workflows for processing MS^1 and MS/MS data from multiplexed LC-HRMS experiments.


Key Features:

  • Comprehensive DIA data processing workflow: Processes full-scan MS^1 and MS/MS DIA data from multiplexed liquid chromatography high-resolution mass spectrometry (LC-HRMS) experiments.
  • Support for multiplexing strategies: Supports analysis strategies for multiplexed DIA datasets across multiplexed LC-HRMS experiments.
  • Enhanced MS/MS processing for stepped collision energies: Includes functions to process MS/MS data acquired with stepped collision energies to improve fragmentation-based annotation.
  • Performance scoring system: Provides a performance scoring system to assess the quality of metabolite annotations.
  • Batch job analysis capability: Enables batch job analysis for high-throughput processing of large metabolomic datasets.

Scientific Applications:

  • Biological validation: Applied to human urine, leukemia cell culture, and medium samples acquired on liquid chromatography quadrupole time-of-flight (q-TOF) and quadrupole orbital (q-Orbitrap) instruments.

Methodology:

Processes full-scan MS^1 and MS/MS DIA data from multiplexed LC-HRMS, processes MS/MS from stepped collision energies, computes performance scores for annotations, and supports batch job and recursive retrospective analysis of multiplexed DIA datasets.

Topics

Details

License:
GPL-2.0
Tool Type:
library
Programming Languages:
R
Added:
11/14/2019
Last Updated:
12/28/2020

Operations

Publications

Peris-Díaz MD, Sweeney SR, Rodak O, Sentandreu E, Tiziani S. R-MetaboList 2: A Flexible Tool for Metabolite Annotation from High-Resolution Data-Independent Acquisition Mass Spectrometry Analysis. Metabolites. 2019;9(9):187. doi:10.3390/metabo9090187. PMID:31533242. PMCID:PMC6780920.

PMID: 31533242
PMCID: PMC6780920
Funding: - National Institutes of Health: CA206210-R01, CA189623 - Cancer Prevention and Research Institute of Texas: CPRIT RP180309 - National Science Center of Poland: 2018/31/N/ST4/01909