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Bioinformatics. 2016 Jul 1;32(13):2035-7. doi: 10.1093/bioinformatics/btw091. Epub 2016 Feb 18.

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

Author information

1
Department of Biomedical Informatics and Computational Biology, University of Minnesota, Rochester University of Minnesota Informatics Institute, University of Minnesota, St Paul.
2
Department of Biochemistry, Molecular Biology, and Biophysics.
3
Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA.

Abstract

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.

AVAILABILITY AND IMPLEMENTATION:

http://www.z.umn.edu/ripper

CONTACT:

vanr0014@umn.edu

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
27153682
PMCID:
PMC4920113
DOI:
10.1093/bioinformatics/btw091
[Indexed for MEDLINE]
Free PMC Article

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