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RIPPER: a framework for MS1 only metabolomics and proteomics label-free relative quantification

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Zeitschriftentitel: Bioinformatics
Personen und Körperschaften: Van Riper, Susan K., Higgins, LeeAnn, Carlis, John V., Griffin, Timothy J.
In: Bioinformatics, 32, 2016, 13, S. 2035-2037
Format: E-Article
Sprache: Englisch
veröffentlicht:
Oxford University Press (OUP)
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Zusammenfassung: <jats:title>Abstract</jats:title> <jats:p>Summary: RIPPER is a framework for mass-spectrometry-based label-free relative quantification for proteomics and metabolomics studies. RIPPER combines a series of previously described algorithms for pre-processing, analyte quantification, retention time alignment, and analyte grouping across runs. It is also the first software framework to implement proximity-based intensity normalization. RIPPER produces lists of analyte signals with their unnormalized and normalized intensities that can serve as input to statistical and directed mass spectrometry (MS) methods for detecting quantitative differences between biological samples using MS.</jats:p> <jats:p>Availability and implementation:  http://www.z.umn.edu/ripper.</jats:p> <jats:p>Contact:  vanr0014@umn.edu</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p>
Umfang: 2035-2037
ISSN: 1367-4811
1367-4803
DOI: 10.1093/bioinformatics/btw091