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

Autor: Louise U. Kurt, Eduardo S B Lyra, Tatiana de Arruda Campos Brasil de Souza, Fabio C. Gozzo, Milan A. Clasen, Diogo B. Lima, Paulo C. Carvalho, Marlon D.M. Santos, Emanuella de Castro Andreassa
Rok vydání: 2020
Předmět:
Zdroj: Journal of Proteomics. 225:103864
ISSN: 1874-3919
DOI: 10.1016/j.jprot.2020.103864
Popis: 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.
Databáze: OpenAIRE
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