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Multi-Q: A Fully Automated Tool for Multiplexed Protein Quantitation
Author(s) -
Wen-Ting Lin,
Wei-Neng Hung,
Yi-Hwa Yian,
KunPin Wu,
ChiaLi Han,
YetRan Chen,
YuJu Chen,
Ting-Yi Sung,
Wen-Lian Hsu
Publication year - 2006
Publication title -
journal of proteome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.644
H-Index - 161
eISSN - 1535-3907
pISSN - 1535-3893
DOI - 10.1021/pr060132c
Subject(s) - executable , computer science , software , normalization (sociology) , quantitative proteomics , automation , shotgun proteomics , multiplexing , data mining , proteomics , multiplex , computational biology , bioinformatics , chemistry , biology , programming language , mechanical engineering , telecommunications , biochemistry , sociology , anthropology , engineering , gene
The iTRAQ labeling method combined with shotgun proteomic techniques represents a new dimension in multiplexed quantitation for relative protein expression measurement in different cell states. To expedite the analysis of vast amounts of spectral data, we present a fully automated software package, called Multi-Q, for multiplexed iTRAQ-based quantitation in protein profiling. Multi-Q is designed as a generic platform that can accommodate various input data formats from search engines and mass spectrometer manufacturers. To calculate peptide ratios, the software automatically processes iTRAQ's signature peaks, including peak detection, background subtraction, isotope correction, and normalization to remove systematic errors. Furthermore, Multi-Q allows users to define their own data-filtering thresholds based on semiempirical values or statistical models so that the computed results of fold changes in peptide ratios are statistically significant. This feature facilitates the use of Multi-Q with various instrument types with different dynamic ranges, which is an important aspect of iTRAQ analysis. The performance of Multi-Q is evaluated with a mixture of 10 standard proteins and human Jurkat T cells. The results are consistent with expected protein ratios and thus demonstrate the high accuracy, full automation, and high-throughput capability of Multi-Q as a large-scale quantitation proteomics tool. These features allow rapid interpretation of output from large proteomic datasets without the need for manual validation. Executable Multi-Q files are available on Windows platform at http://ms.iis.sinica.edu.tw/Multi-Q/.

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