DNA microarray normalization methods can remove bias from differential protein expression analysis of 2D difference gel electrophoresis results

Bioinformatics. 2004 Sep 1;20(13):2026-34. doi: 10.1093/bioinformatics/bth193. Epub 2004 Mar 25.


Motivation: Two-dimensional Difference Gel Electrophoresis (DIGE) measures expression differences for thousands of proteins in parallel. In contrast to DNA microarray analysis, however, there have been few systematic studies on the validity of differential protein expression analysis, and the effects of normalization methods have not yet been investigated. To address this need, we assessed a series of same-same comparisons, evaluating how random experimental variance influenced differential expression analysis.

Results: The strong fluctuations observed were reflected in large discrepancies between the distributions of the spot intensities for different gels. Correct normalization for pooling of multiple gels for analysis is, therefore, essential. We show that both dye-specific background levels and the differences in scale of the spot intensity distributions must be accounted for. A variance stabilizing transform that had been developed for DNA microarray analysis combined with a robust Z-score allowed the determination of gel-independent signal thresholds based on the empirical distributions from same-same comparisons. In contrast, similar thresholds holding up to cross-validation could not be proposed for data normalized using methods established in the field of proteomics.

Availability: Software is available on request from the authors.

Supplementary information: There is supplementary material available online at http://www.flychip.org.uk/kreil/pub/2dgels/

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Algorithms*
  • Bayes Theorem
  • Computer Simulation
  • Data Interpretation, Statistical
  • Electrophoresis, Gel, Two-Dimensional / methods*
  • Electrophoresis, Gel, Two-Dimensional / standards
  • Gene Expression Profiling / methods*
  • Gene Expression Profiling / standards
  • Models, Genetic
  • Models, Statistical
  • Oligonucleotide Array Sequence Analysis / methods*
  • Oligonucleotide Array Sequence Analysis / standards
  • Sensitivity and Specificity
  • Sequence Alignment / methods*
  • Sequence Alignment / standards
  • Sequence Analysis, DNA / methods*
  • Sequence Analysis, DNA / standards