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RawVegetable 2.0: Refining XL-MS Data Acquisition through Enhanced Quality Control.

Authors :
Kurt LU
Clasen MA
Biembengut ÍV
Ruwolt M
Liu F
Gozzo FC
Lima DB
Carvalho PC
Source :
Journal of proteome research [J Proteome Res] 2024 Aug 02; Vol. 23 (8), pp. 3141-3148. Date of Electronic Publication: 2024 Feb 01.
Publication Year :
2024

Abstract

We present RawVegetable 2.0, a software tailored for assessing mass spectrometry data quality and fine-tuned for cross-linking mass spectrometry (XL-MS) applications. Building upon the capabilities of its predecessor, RawVegetable 2.0 introduces four main modules, each providing distinct and new functionalities: 1) Pair Finder, which identifies ion doublets characteristic of cleavable cross-linking experiments; 2) Diagnostic Peak Finder, which locates potential reporter ions associated with a specific cross-linker; 3) Precursor Signal Ratio, which computes the ratio between precursor intensity and the total signal in an MS/MS scan; and 4) Xrea, which evaluates spectral quality by analyzing the heterogeneity of peak intensities within a spectrum. These modules collectively streamline the process of optimizing mass spectrometry data acquisition for both Proteomics and XL-MS experiments. RawVegetable 2.0, along with a comprehensive tutorial is freely accessible for academic use at: http://patternlabforproteomics.org/rawvegetable2.

Details

Language :
English
ISSN :
1535-3907
Volume :
23
Issue :
8
Database :
MEDLINE
Journal :
Journal of proteome research
Publication Type :
Academic Journal
Accession number :
38301217
Full Text :
https://doi.org/10.1021/acs.jproteome.3c00791