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

Susan K. Van Riper, LeeAnn Higgins, John V Carlis, Timothy J Griffin

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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. Availability and implementation: http://www.z.umn.edu/ripper.

Original languageEnglish (US)
Pages (from-to)2035-2037
Number of pages3
JournalBioinformatics
Volume32
Issue number13
DOIs
StatePublished - Jul 1 2016

Bibliographical note

Publisher Copyright:
© The Author 2016.

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