MSQuant, an Open Source Platform for Mass Spectrometry-Based Quantitative Proteomics
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MSQuant, an Open Source Platform for Mass Spectrometry-Based Quantitative Proteomics. / Mortensen, Peter; Gouw, Joost W; Olsen, Jesper V; Ong, Shao-En; Rigbolt, Kristoffer T G; Bunkenborg, Jakob; Cox, Ju¨rgen; Foster, Leonard J; Heck, Albert J R; Blagoev, Blagoy; Andersen, Jens S; Mann, Matthias.
In: Journal of Proteome Research, 01.2010.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - MSQuant, an Open Source Platform for Mass Spectrometry-Based Quantitative Proteomics
AU - Mortensen, Peter
AU - Gouw, Joost W
AU - Olsen, Jesper V
AU - Ong, Shao-En
AU - Rigbolt, Kristoffer T G
AU - Bunkenborg, Jakob
AU - Cox, Ju¨rgen
AU - Foster, Leonard J
AU - Heck, Albert J R
AU - Blagoev, Blagoy
AU - Andersen, Jens S
AU - Mann, Matthias
PY - 2010/1
Y1 - 2010/1
N2 - Mass spectrometry-based proteomics 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 .
AB - Mass spectrometry-based proteomics 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 .
U2 - 10.1021/pr900721e
DO - 10.1021/pr900721e
M3 - Journal article
C2 - 19888749
JO - Journal of Proteome Research
JF - Journal of Proteome Research
SN - 1535-3893
ER -
ID: 16275191