PeptideShaker Online

PeptideShaker Online provides processing and interpretation of mass spectrometry-based proteomics data, integrating raw file conversion, peptide and protein identification, quantification, and visualization within the Galaxy platform using SearchGUI and PeptideShaker.


Key Features:

  • Galaxy integration: Integrates with the Galaxy platform and incorporates SearchGUI and PeptideShaker for data processing and analysis.
  • End-to-end workflow: Supports raw file conversion through downstream analysis and visualization for mass spectrometry-based proteomics datasets.
  • Data handling and storage: Provides capabilities for efficient storage and processing of large-scale high-throughput proteomics datasets.
  • Visualization and PTM analysis: Generates visualizations of identification, quantification, and post-translational modification (PTM) results.

Scientific Applications:

  • Protein Identification: Facilitating the identification of proteins from complex biological samples using SearchGUI and PeptideShaker outputs.
  • Quantitative Proteomics: Supporting the quantification of protein abundances across different experimental conditions.
  • Post-translational Modifications (PTMs): Enabling analysis and visualization of PTMs to study protein function and regulation.

Methodology:

Integrates SearchGUI and PeptideShaker within the Galaxy platform and performs raw file conversion, data processing, storage, and visualization.

Topics

Details

License:
Apache-2.0
Cost:
Free of charge
Tool Type:
api
Operating Systems:
Mac, Linux, Windows
Programming Languages:
JavaScript, Java
Added:
4/9/2022
Last Updated:
4/9/2022

Operations

Publications

Farag YM, Horro C, Vaudel M, Barsnes H. PeptideShaker Online: A User-Friendly Web-Based Framework for the Identification of Mass Spectrometry-Based Proteomics Data. Journal of Proteome Research. 2021;20(12):5419-5423. doi:10.1021/acs.jproteome.1c00678. PMID:34709836. PMCID:PMC8650087.

PMID: 34709836
PMCID: PMC8650087
Funding: - Norges Forskningsr??d: 301178 - Bergens Forskningsstiftelse: BFS2016REK02

Documentation