R-MetaboList 2: A Flexible Tool for Metabolite Annotation from High-Resolution Data-Independent Acquisition Mass Spectrometry Analysis.

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2019
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Abstract
Technological advancements have permitted the development of innovative multiplexing strategies for data independent acquisition (DIA) mass spectrometry (MS). Software solutions and extensive compound libraries facilitate the efficient analysis of MS data, regardless of the analytical platform. However, the development of comparable tools for DIA data analysis has significantly lagged. This research introduces an update to the former MetaboList R package and a workflow for full-scan MS and MS/MS DIA processing of metabolomic data from multiplexed liquid chromatography high-resolution mass spectrometry (LC-HRMS) experiments. When compared to the former version, new functions have been added to address isolated MS and MS/MS workflows, processing of MS/MS data from stepped collision energies, performance scoring of metabolite annotations, and batch job analysis were incorporated into the update. The flexibility and efficiency of this strategy were assessed through the study of the metabolite profiles of human urine, leukemia cell culture, and medium samples analyzed by either liquid chromatography quadrupole time-of-flight (q-TOF) or quadrupole orbital (q-Orbitrap) instruments. This open-source alternative was designed to promote global metabolomic strategies based on recursive retrospective research of multiplexed DIA analysis.
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perisdaz2019rmetabolistmetabolites Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Peris-Díaz, Manuel D;Sweeney, Shannon R;Rodak, Olga;Sentandreu, Enrique;Tiziani, Stefano;
Journal Metabolites
Year 2019
DOI
E187
URL
Keywords
metabolomics r programming r-metabolist 2 all ion fragmentation data-independent acquisition full-scan ms/ms processing liquid chromatography high-resolution mass spectrometry targeted analysis untargeted analysis impact resistance cfrp composites graphite fluoride

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