2009
DOI: 10.1021/pr900721e
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MSQuant, an Open Source Platform for Mass Spectrometry-Based Quantitative Proteomics

Abstract: 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… Show more

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Cited by 233 publications
(197 citation statements)
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“…Identification and quantification were performed with Mascot (version 2.2.0, MatrixScience, London, UK) against the EcoProt database (21) and MSQuant version 1.4.3 (22).…”
Section: Lc-ms/ms Analysis Of Complex Samples-lc-ms/msmentioning
confidence: 99%
See 1 more Smart Citation
“…Identification and quantification were performed with Mascot (version 2.2.0, MatrixScience, London, UK) against the EcoProt database (21) and MSQuant version 1.4.3 (22).…”
Section: Lc-ms/ms Analysis Of Complex Samples-lc-ms/msmentioning
confidence: 99%
“…The pre-column was then connected to a 75-m ϫ 25-cm Acclaim PepMap 100 C18, 3 m, 100-Å column (Dionex), where the peptide sample was loaded with 95% solvent A (0.1% formic acid (v/v)) and 5% solvent B (0.1% formic acid, 84% ACN) at a flow rate of 0.400 l/min by the micro pump system. Peptides were eluted with a linear gradient of 5% (22). The data analysis was divided into three steps.…”
Section: Lc-ms/ms Analysis Of Complex Samples-lc-ms/msmentioning
confidence: 99%
“…Data Analysis-For data analysis using MSQuant version 2.0a81 (19) Fig. 4B), phosphopeptides showing significant increases upon SteC transfection were manually validated using MSQuant.…”
Section: Cloning and Purification Of Stec-mentioning
confidence: 99%
“…Availability of appropriate software is becoming less of an issue, because packages accepting various labeling formats are being developed Mortensen et al 2010).…”
Section: Quantitative Proteomicsmentioning
confidence: 99%