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

被引:30
作者
Hartler, Juergen
Thallinger, Gerhard G.
Stocker, Gernot
Sturn, Alexander
Burkard, Thomas R.
Koerner, Erik
Rader, Robert
Schmidt, Andreas
Mechtler, Karl
Trajanoski, Zlatko
机构
[1] Graz Univ Technol, Christian Doppler Lab Genom & Bioinformat, Inst Genom & Bioinformat, A-8010 Graz, Austria
[2] Austrian Res Ctrs GmbH, ARC, eHealth Syst, A-8020 Graz, Austria
[3] FH Joanneum, A-8605 Kapfenberg, Austria
[4] Christian Doppler Lab Proteome Anal, A-1030 Vienna, Austria
[5] Res Inst Mol Pathol, A-1030 Vienna, Austria
关键词
D O I
10.1186/1471-2105-8-197
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: 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. Results: 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 Conclusion: 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.
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页数:13
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