Martin-Magniette Marie-Laure, Aubert Julie, Bar-Hen Avner, Elftieh Samira, Magniette Frederic, Renou Jean-Pierre, Daudin Jean-Jacques
UMR AgroParisTech-INRA MIA 518, 75231 Paris Cedex05, France.
BMC Bioinformatics. 2008 Apr 28;9:216. doi: 10.1186/1471-2105-9-216.
Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis) allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data.
We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2.
The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.
大多数微阵列研究使用一种或两种染料进行标记，这使得一个或两个样本能够在同一张载玻片上进行杂交。在这类实验中，最常用的染料是Cy3和Cy5。该技术（染料标记、扫描仪和图像分析）最近的改进使得能够同时对多达四个样本进行杂交。另外两种染料是Alexa488和Alexa494。三靶点或四靶点技术非常有前景，因为它在实验设计中具有更大的灵活性，在比较不同条件诱导的基因表达时能提高统计功效，并且能减少载玻片的使用数量。然而，针对此类数据的统计分析方法很少被提出。此外，全局染料效应的局部加权回归（lowess）校正仅适用于双色实验，即使可以推导其应用，也不能对原始数据进行同时校正。
我们为三靶点实验提出了一种两步归一化程序。首先评估染料渗漏情况，并在必要时进行校正。然后使用广义局部加权回归程序对每个通道的信号进行归一化，以校正全局染料偏差。通过三重复自身实验以及比较三靶点和双色实验的结果来验证归一化程序。尽管重点是三靶点微阵列，但所提出的方法可用于对在同一阵列上共同杂交的p个不同标记靶点进行归一化，其中p大于2的任何值均可。
所提出的归一化程序是有效的：技术偏差得以减少，在差异表达基因分析中假阳性数量得到控制，并且三靶点实验比相应的双色实验更具功效。通过同时杂交两个以上样本，微阵列实验还有改进的空间。
