Journal
JOURNAL OF PROTEOME RESEARCH
Volume 9, Issue 1, Pages 393-403Publisher
AMER CHEMICAL SOC
DOI: 10.1021/pr900721e
Keywords
Mass spectrometry-based proteomics; proteomics software; protein identification; protein quantitation; stable isotope labeling
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Funding
- Danish National Research Foundation
- European Commission [HEALTH-F4-2008-201648/PROSPECTS]
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Mass spectrometry-based proteom ics critically depends on algorithms for data interpretation. A current bottleneck in the rapid advance of proteomics technology is the closed nature and slow development cycle of vendor-supplied software solutions. We have created an open source software environment, called MSQuant, which allows visualization and validation of peptide identification results directly on the raw mass spectrometric data. MSQuant iteratively recalibrates MS data thereby significantly increasing mass accuracy leading to fewer false positive peptide identifications. Algorithms to increase data quality include an MS(3) score for peptide identification and a post-translational modification (PTM) score that determines the probability that a modification such as phosphorylation is placed at a specific residue in an identified peptide. MSQuant supports relative protein quantitation based on precursor ion intensities, including element labels (e.g., (15)N), residue labels (e.g., SILAC and ICAT), termini labels (e.g., (18)O), functional group labels (e.g., mTRAQ), and label-free ion intensity approaches. MSQuant is available, including an installer and supporting scripts, at http://msquant.sourceforge.net.
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