PeptideShaker



PeptideShaker 1.1.3:: DESCRIPTION. PeptideShaker is a search engine independent platform for visualization of peptide and protein identification results from multiple search engines. Tandem identification statistics, PeptideShaker PSM score and confidence along with PepQuery-generated score, p-value, confidence and Lorikeet and Unipept metrics. Pseudomonas monteilii is a Gram-negative, rod-shaped, motile bacterium isolated from human bronchial aspirate.

  1. Peptideshaker
  2. Peptideshaker
  3. Peptideshaker Github
  4. Peptide Shaker Software
  5. Peptideshaker Cli
PeptideShaker

PeptideShaker not only allows processing, analysis and interpretation of freshly acquired data, but also automates the conversion of these data into comprehensively annotated mzIdentML files. PeptideShaker is a search engine independent platform for interpretation of proteomics identification results from multiple search engines, currently supporting X!Tandem, MS-GF+, MS Amanda, OMSSA, MyriMatch, Comet, Tide, Mascot, Andromeda and mzIdentML. By combining the results from multiple search engines, while re-calculating PTM localization scores and redoing the protein inference.

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After 3 years of work, SearchGUI (SG),a tool that performs protein identification using various search engines, and PeptideShaker (PS) for protein identification (which uses SearchGUI results) have been deeply updated and released in new major versions: 4.0.7 and 2.0.5, respectively.Furthermore, two new utility tools have been added to make the overall workflow more flexible:

  • Identification parameters for creating parameter files reusable by both SG and PS.
  • FastaCLI, which appends decoy sequences to a FASTA file in a format readable by SG and PS.

The number of changes and improvements made is large, a few highlights:

SearchGUI

  • Support for spectrum files in mzML format.
  • Search engines updated to the most recent versions. Options updated accordingly.
  • FASTA file is now out of the search parameters.
  • Many more supported search engines parameters.
  • More detailed release notes.

PeptideShaker

  • Support for spectrum files in mzML format.
  • Internal refactoring, new internal database and more efficient data management.
  • Reduced file sizes and memory load.
  • More detailed release notes.

Thanks, Carlos Horro Marcos for your awesome work on the Galaxy integration.

Author
Marc Vaudel, Julia M Burkhart, René P Zahedi, Eystein Oveland, Frode S Berven, Albert Sickmann, Lennart Martens(UGent) and Harald Barsnes(UGent)
Organization
Project
Keywords
PROTEINS, IDENTIFICATIONS, DATA SUBMISSION, PRIDE CONVERTER

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Peptideshaker

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Citation

Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-5928839

PeptideShaker
MLA
Vaudel, Marc et al. “PeptideShaker Enables Reanalysis of MS-derived Proteomics Data Sets.” NATURE BIOTECHNOLOGY 33.1 (2015): 22–24. Print.
APA
Vaudel, M., Burkhart, J. M., Zahedi, R. P., Oveland, E., Berven, F. S., Sickmann, A., Martens, L., et al. (2015). PeptideShaker enables reanalysis of MS-derived proteomics data sets. NATURE BIOTECHNOLOGY, 33(1), 22–24.

Peptideshaker

Chicago author-date
Vaudel, Marc, Julia M Burkhart, René P Zahedi, Eystein Oveland, Frode S Berven, Albert Sickmann, Lennart Martens, and Harald Barsnes. 2015. “PeptideShaker Enables Reanalysis of MS-derived Proteomics Data Sets.” Nature Biotechnology 33 (1): 22–24.
Chicago author-date (all authors)
Vaudel, Marc, Julia M Burkhart, René P Zahedi, Eystein Oveland, Frode S Berven, Albert Sickmann, Lennart Martens, and Harald Barsnes. 2015. “PeptideShaker Enables Reanalysis of MS-derived Proteomics Data Sets.” Nature Biotechnology 33 (1): 22–24.
Vancouver

Peptideshaker Github

Vaudel M, Burkhart JM, Zahedi RP, Oveland E, Berven FS, Sickmann A, et al. PeptideShaker enables reanalysis of MS-derived proteomics data sets. NATURE BIOTECHNOLOGY. 2015;33(1):22–4.

Peptide Shaker Software

IEEE

Peptideshaker Cli

M. Vaudel et al., “PeptideShaker enables reanalysis of MS-derived proteomics data sets,” NATURE BIOTECHNOLOGY, vol. 33, no. 1, pp. 22–24, 2015.
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