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