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