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MStractor: R Workflow Package for Enhancing Metabolomics Data Pre-Processing and Visualization

Authors :
Luca Nicolotti
Jeremy Hack
Markus Herderich
Natoiya Lloyd
Source :
Metabolites, Vol 11, Iss 8, p 492 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Untargeted metabolomics experiments for characterizing complex biological samples, conducted with chromatography/mass spectrometry technology, generate large datasets containing very complex and highly variable information. Many data-processing options are available, however, both commercial and open-source solutions for data processing have limitations, such as vendor platform exclusivity and/or requiring familiarity with diverse programming languages. Data processing of untargeted metabolite data is a particular problem for laboratories that specialize in non-routine mass spectrometry analysis of diverse sample types across humans, animals, plants, fungi, and microorganisms. Here, we present MStractor, an R workflow package developed to streamline and enhance pre-processing of metabolomics mass spectrometry data and visualization. MStractor combines functions for molecular feature extraction with user-friendly dedicated GUIs for chromatographic and mass spectromerty (MS) parameter input, graphical quality-control outputs, and descriptive statistics. MStractor performance was evaluated through a detailed comparison with XCMS Online. The MStractor package is freely available on GitHub at the MetabolomicsSA repository.

Details

Language :
English
ISSN :
22181989
Volume :
11
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Metabolites
Publication Type :
Academic Journal
Accession number :
edsdoj.1c21b91b9cb046ffbf841972767d5b18
Document Type :
article
Full Text :
https://doi.org/10.3390/metabo11080492