MSeasy
Computational Tool
FAIR Metrics
0 evaluations
General Information
DescriptionUnsupervised and untargeted GC-MS data processing
Homepagehttp://cran.r-project.org/web/packages/MSeasy/index.html
Publications
MSeasy: unsupervised and untargeted GC-MS data processing
Florence Nicolè; Yann Guitton; Elodie A. Courtois; Sandrine Moja; Laurent Legendre; Martine Hossaert-McKey
Summary: MSeasy performs unsupervised data mining on gas chromatography–mass spectrometry data. It detects putative compounds within complex metabolic mixtures through the clustering of mass spectra. Retention times or retention indices are used after clustering, together with other validation criteria, for quality control of putative compounds. The package generates a fingerprinting or profiling matrix compatible with NIST mass spectral search program and ARISTO webtool (Automatic Reduction of Ion Spectra To Ontology) for molecule identification. Most commonly used file formats, NetCDF, mzXML and ASCII, are acceptable. A graphical and user-friendly interface, MSeasyTkGUI, is available for R novices.
Availability: MSeasy and MSeasytkGUI are implemented as R packages available at http://cran.r-project.org/web/packages/MSeasy/index.html and http://cran.r-project.org/web/packages/MSeasyTkGUI/index.html
Contact: florence.nicole@univ-st-etienne.fr
Supplementary information: Additional information, self-guided tutorials and demonstration data are available on the web site: http://sites.google.com/site/rpackagemseasy/home. Workflow of MSeasy is available in supplementary material
Metrics:
Canned Analyses generated by the tool
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Datasets analyzed by the tool
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