Automated Proteomics Pipeline – an easy-to-use and free proteomics processing infrastructure
Proteomics is surrounded by a thriving open-source eco-system. These software tools are often powerful and evolve quickly but they are not user-friendly. Likewise work with large datasets or more thorough profiling of research data quickly increases demands for processing power. The KTH developed Automated Proteomics Pipeline (APP) aims to resolve these issues and is designed for researchers without access to specific computational infrastructure or specialized IT departments.
Erik Malm (School of Biotechnology, Royal Institute of Technology, Stockholm, Sweden)
Jonas Bergquist (Dept. of Chemistry of Uppsala University and SciLifeLab, Uppsala, Sweden)
Thomas Kieselbach (Dept. of Chemistry of Umeå University and KBC proteomics facility, Umeå, Sweden)
Contact Thomas Kieselbach, email: email@example.com . The last day to register is January 8, 2015.
- A quick view of MS based proteomics and the key open-source tools included with APP.
- A view of APPs task structure and how to construct your own tasks.
- An overview on APPs infrastructure and instructions on how to utilize local computers and commodity computational grids to dynamically scale processing power.
This will be followed by practical examples of several proteomics schemes:
- Processing of mass-spectrometry data utilizing multiple database-search engines and validation using PeptideProphet, iProphet and ProteinProphet. Validation of identified post-translational modifications using PTM prophet. -Quantification of identified proteins using unlabeled methods (spectral counting) as well as labeled methods (iTRAQ and SILAC).
- Constructing and utilizing spectral libraries for quickly profiling large datasets for previously identified proteins and post-translational modifications
More information and how to download and install the APP software can be found in the column to the right.