Literature DB >> 22909347

Find pairs: the module for protein quantification of the PeakQuant software suite.

Martin Eisenacher1, Michael Kohl, Sebastian Wiese, Romano Hebeler, Helmut E Meyer, Bettina Warscheid, Christian Stephan.   

Abstract

Accurate quantification of proteins is one of the major tasks in current proteomics research. To address this issue, a wide range of stable isotope labeling techniques have been developed, allowing one to quantitatively study thousands of proteins by means of mass spectrometry. In this article, the FindPairs module of the PeakQuant software suite is detailed. It facilitates the automatic determination of protein abundance ratios based on the automated analysis of stable isotope-coded mass spectrometric data. Furthermore, it implements statistical methods to determine outliers due to biological as well as technical variance of proteome data obtained in replicate experiments. This provides an important means to evaluate the significance in obtained protein expression data. For demonstrating the high applicability of FindPairs, we focused on the quantitative analysis of proteome data acquired in (14)N/(15)N labeling experiments. We further provide a comprehensive overview of the features of the FindPairs software, and compare these with existing quantification packages. The software presented here supports a wide range of proteomics applications, allowing one to quantitatively assess data derived from different stable isotope labeling approaches, such as (14)N/(15)N labeling, SILAC, and iTRAQ. The software is publicly available at http://www.medizinisches-proteom-center.de/software and free for academic use.

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Year:  2012        PMID: 22909347      PMCID: PMC3437042          DOI: 10.1089/omi.2011.0140

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  51 in total

1.  A novel multifunctional labeling reagent for enhanced protein characterization with mass spectrometry.

Authors:  E C Peters; D M Horn; D C Tully; A Brock
Journal:  Rapid Commun Mass Spectrom       Date:  2001       Impact factor: 2.419

2.  Accurate quantitation of protein expression and site-specific phosphorylation.

Authors:  Y Oda; K Huang; F R Cross; D Cowburn; B T Chait
Journal:  Proc Natl Acad Sci U S A       Date:  1999-06-08       Impact factor: 11.205

3.  A correlation algorithm for the automated quantitative analysis of shotgun proteomics data.

Authors:  Michael J MacCoss; Christine C Wu; Hongbin Liu; Rovshan Sadygov; John R Yates
Journal:  Anal Chem       Date:  2003-12-15       Impact factor: 6.986

4.  ZoomQuant: an application for the quantitation of stable isotope labeled peptides.

Authors:  Brian D Halligan; Ronit Y Slyper; Simon N Twigger; Wayne Hicks; Michael Olivier; Andrew S Greene
Journal:  J Am Soc Mass Spectrom       Date:  2005-01-13       Impact factor: 3.109

5.  Protein labeling by iTRAQ: a new tool for quantitative mass spectrometry in proteome research.

Authors:  Sebastian Wiese; Kai A Reidegeld; Helmut E Meyer; Bettina Warscheid
Journal:  Proteomics       Date:  2007-02       Impact factor: 3.984

6.  Protease-catalyzed incorporation of 18O into peptide fragments and its application for protein sequencing by electrospray and matrix-assisted laser desorption/ionization mass spectrometry.

Authors:  M Schnölzer; P Jedrzejewski; W D Lehmann
Journal:  Electrophoresis       Date:  1996-05       Impact factor: 3.535

7.  Acid-labile isotope-coded extractants: a class of reagents for quantitative mass spectrometric analysis of complex protein mixtures.

Authors:  Yongchang Qiu; Eric A Sousa; Rodney M Hewick; Jack H Wang
Journal:  Anal Chem       Date:  2002-10-01       Impact factor: 6.986

8.  Global internal standard technology for comparative proteomics.

Authors:  Asish Chakraborty; Fred E Regnier
Journal:  J Chromatogr A       Date:  2002-03-08       Impact factor: 4.759

9.  A reciprocal 15N-labeling proteomic analysis of expanding Arabidopsis leaves subjected to osmotic stress indicates importance of mitochondria in preserving plastid functions.

Authors:  Aleksandra Skirycz; Samy Memmi; Stefanie De Bodt; Katrien Maleux; Toshihiro Obata; Alisdair R Fernie; Bart Devreese; Dirk Inzé
Journal:  J Proteome Res       Date:  2011-01-25       Impact factor: 4.466

10.  Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells.

Authors:  David Bouyssié; Anne Gonzalez de Peredo; Emmanuelle Mouton; Renaud Albigot; Lucie Roussel; Nathalie Ortega; Corinne Cayrol; Odile Burlet-Schiltz; Jean-Philippe Girard; Bernard Monsarrat
Journal:  Mol Cell Proteomics       Date:  2007-05-28       Impact factor: 5.911

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  2 in total

1.  Bioinformatics challenges and solutions in proteomics as quantitative methods mature.

Authors:  Andrew R Jones
Journal:  OMICS       Date:  2012-07-17

Review 2.  Quantitative Proteomics Using Isobaric Labeling: A Practical Guide.

Authors:  Xiulan Chen; Yaping Sun; Tingting Zhang; Lian Shu; Peter Roepstorff; Fuquan Yang
Journal:  Genomics Proteomics Bioinformatics       Date:  2022-01-08       Impact factor: 6.409

  2 in total

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