Kreil David P, Karp Natasha A, Lilley Kathryn S
Department of Genetics/Inference Group (Cavendish Laboratory), University of Cambridge, Cambridge, UK.
Bioinformatics. 2004 Sep 1;20(13):2026-34. doi: 10.1093/bioinformatics/bth193. Epub 2004 Mar 25.
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.
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.
Software is available on request from the authors.
There is supplementary material available online at http://www.flychip.org.uk/kreil/pub/2dgels/
二维差异凝胶电泳（DIGE）可并行测量数千种蛋白质的表达差异。然而，与DNA微阵列分析不同，关于差异蛋白质表达分析的有效性几乎没有系统研究，并且尚未研究归一化方法的效果。为满足这一需求，我们评估了一系列相同样本比较，以评估随机实验方差如何影响差异表达分析。
观察到的强烈波动反映在不同凝胶上斑点强度分布之间的巨大差异中。因此，对用于分析的多个凝胶进行正确归一化至关重要。我们表明，必须同时考虑染料特异性背景水平和斑点强度分布尺度的差异。为DNA微阵列分析开发的方差稳定变换与稳健的Z分数相结合，使得能够基于相同样本比较的经验分布确定与凝胶无关的信号阈值。相比之下，对于使用蛋白质组学领域建立的方法归一化的数据，无法提出适用于交叉验证的类似阈值。
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