Song Jun S, Maghsoudi Kaveh, Li Wei, Fox Edward, Quackenbush John, Shirley Liu X
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.
Bioinformatics. 2007 Apr 15;23(8):966-71. doi: 10.1093/bioinformatics/btm043. Epub 2007 Mar 1.
New generation Affymetrix oligonucleotide microarrays often have blob-like image defects that will require investigators to either repeat their hybridization assays or analyze their data with the defects left in place. We investigated the effect of analyzing a spike-in experiment on Affymetrix ENCODE tiling arrays in the presence of simulated blobs covering between 1 and 9% of the array area. Using two different ChIP-chip tiling array analysis programs (Affymetrix tiling array software, TAS, and model-based analysis of tiling arrays, MAT), we found that even the smallest blob defects significantly decreased the sensitivity and increased the false discovery rate (FDR) of the spike-in target prediction.
We introduced a new software tool, the microarray blob remover (MBR), which allows rapid visualization, detection and removal of various blob defects from the .CEL files of different types of Affymetrix microarrays. It is shown that using MBR significantly improves the sensitivity and FDR of a tiling array analysis compared to leaving the affected probes in the analysis.
The MBR software and the sample array .CEL files used in this article are available at: http://liulab.dfci.harvard.edu/Software/MBR/MBR.htm
新一代Affymetrix寡核苷酸微阵列常常存在斑点状图像缺陷，这将要求研究人员要么重复杂交实验，要么在保留缺陷的情况下分析数据。我们研究了在存在覆盖阵列面积1%至9%的模拟斑点的情况下，分析Affymetrix ENCODE平铺阵列上的掺入实验的影响。使用两种不同的ChIP芯片平铺阵列分析程序（Affymetrix平铺阵列软件，TAS，以及平铺阵列的基于模型的分析，MAT），我们发现即使是最小的斑点缺陷也会显著降低掺入靶标预测的灵敏度并增加错误发现率（FDR）。
我们引入了一种新的软件工具，微阵列斑点去除器（MBR），它可以快速可视化、检测并从不同类型的Affymetrix微阵列的.CEL文件中去除各种斑点缺陷。结果表明，与在分析中保留受影响的探针相比，使用MBR可显著提高平铺阵列分析的灵敏度和FDR。
MBR软件和本文中使用的样本阵列.CEL文件可在以下网址获得：http://liulab.dfci.harvard.edu/Software/MBR/MBR.htm
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