RawVegetable - A data assessment tool for proteomics and cross-linking mass spectrometry experiments

J Proteomics. 2020 Aug 15:225:103864. doi: 10.1016/j.jprot.2020.103864. Epub 2020 Jun 9.

Abstract

We present RawVegetable, a software for mass spectrometry data assessment and quality control tailored toward shotgun proteomics and cross-linking experiments. RawVegetable provides four main modules with distinct features: (A) The charge state chromatogram that independently displays the ion current for each charge state; useful for optimizing the chromatography for highly charged ions and with lower XIC values such as those typically found in cross-linking experiments. (B) The XL-Artefact determination, which flags possible noncovalently associated peptides. (C) The TopN density estimation, for detecting retention time intervals of under or over-sampling, and (D) The chromatography reproducibility module, which provides pairwise comparisons between multiple experiments. RawVegetable, a tutorial, and the example data are freely available for academic use at: http://patternlabforproteomics.org/rawvegetable. SIGNIFICANCE: Chromatography optimization is a critical step for any shotgun proteomic or cross-linking mass spectrometry experiment. Here, we present a nifty solution with several key features, such as displaying individual charge state chromatograms, highlighting chromatographic regions of under- or over-sampling and checking for reproducibility.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Mass Spectrometry
  • Peptides
  • Proteomics*
  • Reproducibility of Results
  • Software*

Substances

  • Peptides