MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

• Published in: BMC bioinformatics Vol. 8; no. 1; p. 197
• Main Authors: Hartler, Jürgen, Thallinger, Gerhard G, Stocker, Gernot, Sturn, Alexander, Burkard, Thomas R, Körner, Erik, Rader, Robert, Schmidt, Andreas, Mechtler, Karl, Trajanoski, Zlatko
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 13.06.2007; BioMed Central; BMC
• Subjects: Amino Acid Sequence; Chromatography, Liquid - methods; Database Management Systems; Databases, Protein; Information Storage and Retrieval - methods; Mass Spectrometry - methods; Molecular Sequence Data; Peptide Mapping - methods; Product/service Evaluations; Proteome - chemistry; Proteome - metabolism; Sequence Analysis, Protein - methods; Software; Software Design; Systems Integration; User-Computer Interface; Austria
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/1471-2105-8-197

The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches. We have developed the MAss SPECTRometry Analysis System (MASPECTRAS), a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo) relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI). Analysis modules include: 1) import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2) peptide validation, 3) clustering of proteins based on Markov Clustering and multiple alignments; and 4) quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio). The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE). MASPECTRAS is freely available at http://genome.tugraz.at/maspectras Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community.