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


BACKGROUND
Software is available on request from the authors.


BACKGROUND
There is supplementary material available online at http://www.flychip.org.uk/kreil/pub/2dgels/
Kreil
David P
DP
Department of Genetics/Inference Group (Cavendish Laboratory), University of Cambridge, Cambridge, UK. D.Kreil@gen.cam.ac.uk
Karp
Natasha A
NA
Lilley
Kathryn S
KS
D000465:Algorithms; D001499:Bayes Theorem; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods* / Q000592:standards; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000592:standards; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods* / Q000592:standards; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000592:standards