Literature DB >> 21187240

Differential analysis of 2D gel images.

Feng Li1, Françoise Seillier-Moiseiwitsch.   

Abstract

Two-dimensional polyacrylomide gel electrophoresis remains a popular and powerful tool for identifying proteins that are differentially expressed across treatment conditions. Due to the overwhelming number of proteins and the tremendous variation shown in gel images, the differential analysis of 2D gel images is challenging. While commercial software packages are available for such analysis, they require considerable human intervention for spot detection and matching. Moreover, the quantitative comparison across groups of gels is based on simple classical tests that often do not fully account for the experimental design. We developed software with a graphical user interface, RegStatGel, which implements a novel statistical algorithm for identifying differentially expressed proteins. Unlike current commercial software packages, it is free, open-source, easy to use and almost fully automated. It also provides more advanced statistical tools. More importantly, by using a master watershed map, RegStatGel bypasses the spot-matching procedure, which is a time-consuming bottleneck in gel image analysis. The software is freely available for academic use and has been tested in Matlab 7.01 under Windows XP. Detailed instructions on how to use RegStatGel to analyze 2D gel images are provided.
© 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21187240     DOI: 10.1016/B978-0-12-381270-4.00021-4

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  2 in total

1.  RegStatGel: proteomic software for identifying differentially expressed proteins based on 2D gel images.

Authors:  Feng Li; Françoise Seillier-Moiseiwitsch
Journal:  Bioinformation       Date:  2011-08-02

2.  Spot quantification in two dimensional gel electrophoresis image analysis: comparison of different approaches and presentation of a novel compound fitting algorithm.

Authors:  Jan M Brauner; Teja W Groemer; Armin Stroebel; Simon Grosse-Holz; Timo Oberstein; Jens Wiltfang; Johannes Kornhuber; Juan Manuel Maler
Journal:  BMC Bioinformatics       Date:  2014-06-11       Impact factor: 3.169

  2 in total

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