title: RIPPER: a framework for MS1 only metabolomics and proteomics label-free relative quantification.
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.
  
  
  
  http://www.z.umn.edu/ripper
  
  
  
  vanr0014@umn.edu
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Biomedical Informatics and Computational Biology, University of Minnesota, Rochester University of Minnesota Informatics Institute, University of Minnesota, St Paul.
authors.forename: Susan K
authors.initials: SK
authors.lastname: Van Riper
authors.affiliation: Department of Biochemistry, Molecular Biology, and Biophysics.
authors.forename: LeeAnn
authors.initials: L
authors.lastname: Higgins
authors.affiliation: Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
authors.forename: John V
authors.initials: JV
authors.lastname: Carlis
authors.affiliation: Department of Biochemistry, Molecular Biology, and Biophysics.
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Griffin
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D006801:Humans; D013058:Mass Spectrometry; D055432:Metabolomics; D040901:Proteomics; D012984:Software