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Peter James

Peter James

Professor

Peter James

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

Author

  • Morten Krogh
  • Yingchun Liu
  • Sofia Waldemarson
  • Barbro Valestro
  • Peter James

Summary, in 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.

Department/s

  • Computational Biology and Biological Physics - Has been reorganised
  • Department of Immunotechnology

Publishing year

2007

Language

English

Pages

4235-4244

Publication/Series

Proteomics

Volume

7

Issue

23

Document type

Journal article

Publisher

John Wiley & Sons Inc.

Topic

  • Immunology in the medical area
  • Biophysics

Keywords

  • 2-D gels
  • DIGE
  • dye effects
  • linear mixed model

Status

Published

ISBN/ISSN/Other

  • ISSN: 1615-9861