Kelley Ryan, Feizi Hoda, Ideker Trey
Program in Bioinformatics and Department of Bioengineering, University of California, San Diego 9500 Gilman Drive, La Jolla, CA 92093-0412, USA.
Bioinformatics. 2008 Jan 1;24(1):71-7. doi: 10.1093/bioinformatics/btm347. Epub 2007 Jul 10.
In two-color microarray experiments, well-known differences exist in the labeling and hybridization efficiency of Cy3 and Cy5 dyes. Previous reports have revealed that these differences can vary on a gene-by-gene basis, an effect termed gene-specific dye bias. If uncorrected, this bias can influence the determination of differentially expressed genes.
We show that the magnitude of the bias scales multiplicatively with signal intensity and is dependent on which nucleotide has been conjugated to the fluorescent dye. A method is proposed to account for gene-specific dye bias within a maximum-likelihood error modeling framework. Using two different labeling schemes, we show that correcting for gene-specific dye bias results in the superior identification of differentially expressed genes within this framework. Improvement is also possible in related ANOVA approaches.
A software implementation of this procedure is freely available at http://cellcircuits.org/VERA
在双色微阵列实验中，Cy3和Cy5染料在标记和杂交效率方面存在众所周知的差异。先前的报告显示，这些差异可能因基因而异，这种效应被称为基因特异性染料偏差。如果不进行校正，这种偏差会影响差异表达基因的判定。
我们表明，偏差的大小与信号强度呈乘法关系，并且取决于与荧光染料缀合的是哪种核苷酸。我们提出了一种方法，用于在最大似然误差建模框架内考虑基因特异性染料偏差。使用两种不同的标记方案，我们表明在校正基因特异性染料偏差后，在此框架内能够更优地识别差异表达基因。在相关的方差分析方法中也有可能实现改进。
该程序的软件实现可在http://cellcircuits.org/VERA免费获取。
