Corra is a single, user-friendly, informatic framework, that is simple to use and fully customizable, for the enabling of LC-MS-based quantitative proteomic workflows of any size, able to guide the user seamlessly from MS data generation, through data processing, visualization, and statistical analysis steps, to the identification of differentially abundant or expressed candidate features for prioritized targeted identification by subsequent MS/MS. Corra is for the application of proteomics to the detmination or proteins that are differentially expressed or abundant between samples representing different physiological or disease states by integrating multiple and disparate LC-MS data analysis tools, and integrate them, seamlessly, with common statistical packages to allow for better comparison between differently-processed datasets, via the addition of statistical measures of confidence and error rates. The integration of tools was achieve via AMPL (Annotated Putative peptide Markup Language) and the various parsers, and in the current build of Corra, we have implemented SpecArray and SuperHirn. Current distributed Corra contains APML adapted open source of SpecArray and SuperHirn. Corra and its biological application is published in the BMC Bioinformatics 2008 9:542 and be accessible by(Brusniak, et. el.).
Detailed information on the work flow has been published:
[http://www.biomedcentral.com/1471-2105/9/542 Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics Mi-Youn Brusniak, Bernd Bodenmiller, David Campbell, Kelly Cooke, James Eddes, Andrew Garbutt, Hollis Lau, Simon Letarte, Lukas N Mueller, Vagisha Sharma, Olga Vitek, Ning Zhang, Ruedi Aebersold and Julian D Watts]
Installation guide, source codes and example data sets are in 
Feedback and Questions
Please join the Corra discussion group for feature requests, questions and bug reports.
Mi-Youn Brusniak, Ph.D. 1441 North 34th St. Seattle, WA 98103 USA email@example.com