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Analysis of DIGE data using a linear mixed model allowing for protein-specific dye effects

Author:
  • Morten Krogh
  • Sofia Waldemarson
  • Celine Fernandez
  • Barbro Valestro
  • Peter James
Publishing year: 2007
Language: English
Pages: 4235-4244
Publication/Series: Proteomics
Volume: 7
Issue: 23
Document type: Journal article
Publisher: John Wiley & Sons

Abstract english

Abstract in Undetermined

Differential in-gel electrophoresis (DIGE) experiments allow three protein samples to be run per gel. The three samples are labeled with the spectrally resolvable fluorescent dyes, Cy2, Cy3, and Cy5, respectively. Here, we show that protein-specific dye effects exist, and we present a linear mixed model for analysis of DIGE data which takes dye effects into account. A Java implementation of the model, called DIGEanalyzer, is freely available at http://bioinfo.thep.lu.se/digeanalyzer.html. Three DIGE experiments from our laboratory, with 173, 64, and 24 gels, respectively, were used to quantify and verify the dye effects. DeCyder 5.0 and 6.5 were used for spot detection and matching. The fractions of proteins with a statistically significant (0.001 level) dye effect were 19, 34, and 23%, respectively. The fractions of proteins with a dye effect above 1.4-fold change were 1, 4, and 6%, respectively. The median magnitude of the dye effect was 1.07-fold change for Cy5 versus Cy3 and 1.16-fold change for Cy3 versus Cy2. The maximal dye effect was a seven-fold change. The dye effects of spots corresponding to the same protein tend to be similar within each of the three experiments, and to a smaller degree across experiments.

Keywords

  • Immunology in the medical area
  • Biophysics
  • 2-D gels
  • DIGE
  • dye effects
  • linear mixed model

Other

Published
  • CREATE Health
  • Hypertension and Cardiovascular Disease
  • ISSN: 1615-9861
Peter James
E-mail: peter.james [at] immun.lth.se

Professor

Department of Immunotechnology

+46 46 222 14 96

+46 70 247 79 60

MV406411E1

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