Literature DB >> 33950509

Automated Workflow for Peptide-Level Quantitation from DIA/SWATH-MS Data.

Shubham Gupta1,2, Hannes Röst3,4.   

Abstract

Data-independent acquisition (DIA) is a powerful method to acquire spectra from all ionized precursors of a sample. Considering the complexity of the highly multiplexed spectral data, sophisticated workflows have been developed to obtain peptides quantification. Here we describe an open-source and easy-to-use workflow to obtain a quantitative matrix from multiple DIA runs. This workflow requires as prior information an "assay library," which contains the MS coordinates of peptides. It consists of OpenSWATH, pyProphet, and DIAlignR software. For the ease of installation and to isolate operating system-related dependency, docker-based containerization is utilized in this workflow.

Keywords:  DIA; DIAlignR; Data-independent acquisition; OpenSWATH; Retention time alignment; SWATH-MS; pyProphet

Year:  2021        PMID： 33950509     DOI： 10.1007/978-1-0716-1024-4_31

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN： 1064-3745


  12 in total

1.  Quantitative proteogenomics of human pathogens using DIA-MS.

Authors:  Lars Malmström; Anahita Bakochi; Gabriel Svensson; Ola Kilsgård; Henrik Lantz; Ann Cathrine Petersson; Simon Hauri; Christofer Karlsson; Johan Malmström
Journal:  J Proteomics       Date:  2015-09-14       Impact factor: 4.044

2.  Building high-quality assay libraries for targeted analysis of SWATH MS data.

Authors:  Olga T Schubert; Ludovic C Gillet; Ben C Collins; Pedro Navarro; George Rosenberger; Witold E Wolski; Henry Lam; Dario Amodei; Parag Mallick; Brendan MacLean; Ruedi Aebersold
Journal:  Nat Protoc       Date:  2015-02-12       Impact factor: 13.491

3.  Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.

Authors:  Siegfried Gessulat; Tobias Schmidt; Daniel Paul Zolg; Patroklos Samaras; Karsten Schnatbaum; Johannes Zerweck; Tobias Knaute; Julia Rechenberger; Bernard Delanghe; Andreas Huhmer; Ulf Reimer; Hans-Christian Ehrlich; Stephan Aiche; Bernhard Kuster; Mathias Wilhelm
Journal:  Nat Methods       Date:  2019-05-27       Impact factor: 28.547

4.  High-quality MS/MS spectrum prediction for data-dependent and data-independent acquisition data analysis.

Authors:  Shivani Tiwary; Roie Levy; Petra Gutenbrunner; Favio Salinas Soto; Krishnan K Palaniappan; Laura Deming; Marc Berndl; Arthur Brant; Peter Cimermancic; Jürgen Cox
Journal:  Nat Methods       Date:  2019-05-27       Impact factor: 28.547

5.  OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data.

Authors:  Hannes L Röst; George Rosenberger; Pedro Navarro; Ludovic Gillet; Saša M Miladinović; Olga T Schubert; Witold Wolski; Ben C Collins; Johan Malmström; Lars Malmström; Ruedi Aebersold
Journal:  Nat Biotechnol       Date:  2014-03       Impact factor: 54.908

Review 6.  Mass-spectrometric exploration of proteome structure and function.

Authors:  Ruedi Aebersold; Matthias Mann
Journal:  Nature       Date:  2016-09-15       Impact factor: 49.962

7.  Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps.

Authors:  Tiannan Guo; Petri Kouvonen; Ching Chiek Koh; Ludovic C Gillet; Witold E Wolski; Hannes L Röst; George Rosenberger; Ben C Collins; Lorenz C Blum; Silke Gillessen; Markus Joerger; Wolfram Jochum; Ruedi Aebersold
Journal:  Nat Med       Date:  2015-03-02       Impact factor: 53.440

8.  TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

Authors:  Hannes L Röst; Yansheng Liu; Giuseppe D'Agostino; Matteo Zanella; Pedro Navarro; George Rosenberger; Ben C Collins; Ludovic Gillet; Giuseppe Testa; Lars Malmström; Ruedi Aebersold
Journal:  Nat Methods       Date:  2016-08-01       Impact factor: 28.547

9.  A multicenter study benchmarks software tools for label-free proteome quantification.

Authors:  Pedro Navarro; Jörg Kuharev; Ludovic C Gillet; Oliver M Bernhardt; Brendan MacLean; Hannes L Röst; Stephen A Tate; Chih-Chiang Tsou; Lukas Reiter; Ute Distler; George Rosenberger; Yasset Perez-Riverol; Alexey I Nesvizhskii; Ruedi Aebersold; Stefan Tenzer
Journal:  Nat Biotechnol       Date:  2016-10-03       Impact factor: 54.908

10.  Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.

Authors:  George Rosenberger; Isabell Bludau; Uwe Schmitt; Moritz Heusel; Christie L Hunter; Yansheng Liu; Michael J MacCoss; Brendan X MacLean; Alexey I Nesvizhskii; Patrick G A Pedrioli; Lukas Reiter; Hannes L Röst; Stephen Tate; Ying S Ting; Ben C Collins; Ruedi Aebersold
Journal:  Nat Methods       Date:  2017-08-21       Impact factor: 28.547
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  1 in total

1.  Democratizing data-independent acquisition proteomics analysis on public cloud infrastructures via the Galaxy framework.

Authors:  Matthias Fahrner; Melanie Christine Föll; Björn Andreas Grüning; Matthias Bernt; Hannes Röst; Oliver Schilling
Journal:  Gigascience       Date:  2022-02-15       Impact factor: 6.524
  1 in total

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