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MaXIC-Q Web: a fully automated web service using statistical and computational methods for protein quantitation based on stable isotope labeling and LC–MS

Authors :
Han Yin Yang
Yi-Ju Chen
Yu-Ju Chen
Wen-Lian Hsu
Ting-Yi Sung
Chuan-Yih Yu
Ke-Shiuan Lynn
Chih-Chiang Tsou
Yi Hwa Yian
Yin Hao Tsui
Source :
Nucleic Acids Research
Publication Year :
2009
Publisher :
Oxford University Press (OUP), 2009.

Abstract

Isotope labeling combined with liquid chromatography–mass spectrometry (LC–MS) provides a robust platform for analyzing differential protein expression in proteomics research. We present a web service, called MaXIC-Q Web (http://ms.iis.sinica.edu.tw/MaXIC-Q_Web/), for quantitation analysis of large-scale datasets generated from proteomics experiments using various stable isotope-labeling techniques, e.g. SILAC, ICAT and user-developed labeling methods. It accepts spectral files in the standard mzXML format and search results from SEQUEST, Mascot and ProteinProphet as input. Furthermore, MaXIC-Q Web uses statistical and computational methods to construct two kinds of elution profiles for each ion, namely, PIMS (projected ion mass spectrum) and XIC (extracted ion chromatogram) from MS data. Toward accurate quantitation, a stringent validation procedure is performed on PIMSs to filter out peptide ions interfered with co-eluting peptides or noise. The areas of XICs determine ion abundances, which are used to calculate peptide and protein ratios. Since MaXIC-Q Web adopts stringent validation on spectral data, it achieves high accuracy so that manual validation effort can be substantially reduced. Furthermore, it provides various visualization diagrams and comprehensive quantitation reports so that users can conveniently inspect quantitation results. In summary, MaXIC-Q Web is a user-friendly, interactive, robust, generic web service for quantitation based on ICAT and SILAC labeling techniques.

Details

ISSN :
13624962 and 03051048
Volume :
37
Database :
OpenAIRE
Journal :
Nucleic Acids Research
Accession number :
edsair.doi.dedup.....c84a3a8a6471b22ba88d7b2a426cf4d7
Full Text :
https://doi.org/10.1093/nar/gkp476