MSeasy: unsupervised and untargeted GC-MS data processing. Nicolè, F., Guitton, Y., Courtois, E. A., Moja, S., Legendre, L., & Hossaert-McKey, M. 28(17):2278--2280.
MSeasy: unsupervised and untargeted GC-MS data processing [link]Paper  doi  abstract   bibtex   
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
@article{nicole_mseasy:_2012,
	title = {{MSeasy}: unsupervised and untargeted {GC}-{MS} data processing},
	volume = {28},
	issn = {1367-4803, 1460-2059},
	url = {http://bioinformatics.oxfordjournals.org/content/28/17/2278},
	doi = {10.1093/bioinformatics/bts427},
	shorttitle = {{MSeasy}},
	abstract = {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},
	pages = {2278--2280},
	number = {17},
	journaltitle = {Bioinformatics},
	author = {Nicolè, Florence and Guitton, Yann and Courtois, Elodie A. and Moja, Sandrine and Legendre, Laurent and Hossaert-{McKey}, Martine},
	urldate = {2016-07-26},
	date = {2012-01-09},
	langid = {english},
	pmid = {22782550},
	file = {Nicolè et al. - 2012 - MSeasy unsupervised and untargeted GC-MS data pro.pdf:C\:\\Users\\ygu\\Zotero\\storage\\9ADQUTMK\\Nicolè et al. - 2012 - MSeasy unsupervised and untargeted GC-MS data pro.pdf:application/pdf;Snapshot:C\:\\Users\\ygu\\Zotero\\storage\\47FV7CXC\\2278.html:text/html}
}
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