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

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

Research output: Contribution to journalArticlepeer-review


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 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.
Original languageEnglish
Pages (from-to)4235-4244
Issue number23
Publication statusPublished - 2007

Subject classification (UKÄ)

  • Immunology in the medical area
  • Biophysics

Free keywords

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


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