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RAWVEGETABLE 2.0: REFINING XL-MS DATA ACQUISITION THROUGH ENHANCED QUALITY CONTROL
Autor
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Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Proteômica Estrutural e Computacional. Curitiba, PR, Brasil.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Proteômica Estrutural e Computacional. Curitiba, PR, Brasil.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Proteômica Estrutural e Computacional. Curitiba, PR, Brasil.
Department of Chemical Biology, Leibniz. Forschungsinstitut für Molekulare Pharmakologie (FMP). Berlin, Germany.
Department of Chemical Biology, Leibniz. Forschungsinstitut für Molekulare Pharmakologie (FMP). Berlin, Germany.
Universidade Estadual de Campinas. Dalton Mass Spectrometry Laboratory. Campinas, Brasil
Department of Chemical Biology, Leibniz. Forschungsinstitut für Molekulare Pharmakologie (FMP). Berlin, Germany.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Proteômica Estrutural e Computacional. Curitiba, PR, Brasil.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Proteômica Estrutural e Computacional. Curitiba, PR, Brasil.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Proteômica Estrutural e Computacional. Curitiba, PR, Brasil.
Department of Chemical Biology, Leibniz. Forschungsinstitut für Molekulare Pharmakologie (FMP). Berlin, Germany.
Department of Chemical Biology, Leibniz. Forschungsinstitut für Molekulare Pharmakologie (FMP). Berlin, Germany.
Universidade Estadual de Campinas. Dalton Mass Spectrometry Laboratory. Campinas, Brasil
Department of Chemical Biology, Leibniz. Forschungsinstitut für Molekulare Pharmakologie (FMP). Berlin, Germany.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Proteômica Estrutural e Computacional. Curitiba, PR, Brasil.
Resumen en ingles
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
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