MSPrep--summarization, normalization and diagnostics for processing of mass spectrometry-based metabolomic data

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dc.contributor.authorHughes, Grant
dc.contributor.authorCruickshank-Quinn, Charmion
dc.contributor.authorReisdorph, Richard
dc.contributor.authorLutz, Sharon
dc.contributor.authorPetrache, Irina
dc.contributor.authorReisdorph, Nichole
dc.contributor.authorBowler, Nichole
dc.contributor.authorBowler, Russell
dc.contributor.authorKechris, Katerina
dc.contributor.departmentDepartment of Medicine, IU School of Medicineen_US
dc.date.accessioned2016-03-15T13:36:15Z
dc.date.available2016-03-15T13:36:15Z
dc.date.issued2014-01-01
dc.description.abstractMOTIVATION: Although R packages exist for the pre-processing of metabolomic data, they currently do not incorporate additional analysis steps of summarization, filtering and normalization of aligned data. We developed the MSPrep R package to complement other packages by providing these additional steps, implementing a selection of popular normalization algorithms and generating diagnostics to help guide investigators in their analyses.en_US
dc.identifier.citationHughes, G., Cruickshank-Quinn, C., Reisdorph, R., Lutz, S., Petrache, I., Reisdorph, N., … Kechris, K. (2014). MSPrep—Summarization, normalization and diagnostics for processing of mass spectrometry–based metabolomic data. Bioinformatics, 30(1), 133–134. http://doi.org/10.1093/bioinformatics/btt589en_US
dc.identifier.urihttps://hdl.handle.net/1805/8858
dc.publisherOxford University Pressen_US
dc.relation.isversionof10.1093/bioinformatics/btt589en_US
dc.relation.journalBioinformaticsen_US
dc.rightsPublisher Policyen_US
dc.sourcePMCen_US
dc.subjectAlgorithmsen_US
dc.subjectDatabases, Factualen_US
dc.subjectMass Spectrometryen_US
dc.subjectMetabolomics -- Methodsen_US
dc.subjectSoftwareen_US
dc.titleMSPrep--summarization, normalization and diagnostics for processing of mass spectrometry-based metabolomic dataen_US
dc.typeArticleen_US
ul.alternative.fulltexthttp://pubmed.gov/24174567en_US
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