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