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Data Processing and Analysis for DIA-Based Phosphoproteomics Using Spectronaut.
Martinez-Val, Ana; Bekker-Jensen, Dorte Breinholdt; Hogrebe, Alexander; Olsen, Jesper Velgaard.
  • Martinez-Val A; Novo Nordisk Foundation Center for Protein Research, Proteomics Program, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
  • Bekker-Jensen DB; Novo Nordisk Foundation Center for Protein Research, Proteomics Program, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
  • Hogrebe A; Evosep Biosystems, Odense, Denmark.
  • Olsen JV; Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Methods Mol Biol ; 2361: 95-107, 2021.
Article en En | MEDLINE | ID: mdl-34236657
Data-independent acquisition (DIA) for liquid chromatography tandem mass spectrometry (LC-MS/MS) can improve the depth and reproducibility of the acquired proteomics datasets. DIA solves some limitations of the conventional data-dependent acquisition (DDA) strategy, for example, bias in intensity-dependent precursor selection and limited dynamic range. These advantages, together with the recent developments in speed, sensitivity, and resolution in MS technology, position DIA as a great alternative to DDA. Recently, we demonstrated that the benefits of DIA are extendable to phosphoproteomics workflows, enabling increased depth, sensitivity, and reproducibility of our analysis of phosphopeptide-enriched samples. However, computational data analysis of phospho-DIA samples have some specific challenges and requirements to the software and downstream processing workflows. A step-by-step guide to analyze phospho-DIA raw data using either spectral libraries or directDIA in Spectronaut is presented here. Furthermore, a straightforward protocol to perform differential phosphorylation site analysis using the output results from Spectronaut is described.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteómica Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteómica Idioma: En Año: 2021 Tipo del documento: Article