Luscombe Nicholas M, Royce Thomas E, Bertone Paul, Echols Nathaniel, Horak Christine E, Chang Joseph T, Snyder Michael, Gerstein Mark
Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, PO Box 208114, New Haven CT 06520-8114, USA.
Nucleic Acids Res. 2003 Jul 1;31(13):3477-82. doi: 10.1093/nar/gkg628.
DNA microarrays are widely used in biological research; by analyzing differential hybridization on a single microarray slide, one can detect changes in mRNA expression levels, increases in DNA copy numbers and the location of transcription factor binding sites on a genomic scale. Having performed the experiments, the major challenge is to process large, noisy datasets in order to identify the specific array elements that are significantly differentially hybridized. This normally requires aggregating different, often incompatible programs into a multi-step pipeline. Here we present ExpressYourself, a fully integrated platform for processing microarray data. In completely automated fashion, it will correct the background array signal, normalize the Cy5 and Cy3 signals, score levels of differential hybridization, combine the results of replicate experiments, filter problematic regions of the array and assess the quality of individual and replicate experiments. ExpressYourself is designed with a highly modular architecture so various types of microarray analysis algorithms can readily be incorporated as they are developed; for example, the system currently implements several normalization methods, including those that simultaneously consider signal intensity and slide location. The processed data are presented using a web-based graphical interface to facilitate comparison with the original images of the array slides. In particular, Express Yourself is able to regenerate images of the original microarray after applying various steps of processing, which greatly facilities identification of position-specific artifacts. The program is freely available for use at http://bioinfo.mbb.yale.edu/expressyourself.
DNA微阵列在生物学研究中被广泛应用;通过分析单个微阵列载玻片上的差异杂交情况,人们能够在基因组规模上检测mRNA表达水平的变化、DNA拷贝数的增加以及转录因子结合位点的位置。在完成实验后,主要挑战在于处理庞大且有噪声的数据集,以便识别出显著差异杂交的特定阵列元件。这通常需要将不同的、往往不兼容的程序整合到一个多步骤流程中。在此,我们展示了ExpressYourself,一个用于处理微阵列数据的完全集成平台。它以完全自动化的方式校正阵列背景信号,对Cy5和Cy3信号进行归一化,对差异杂交水平进行评分,合并重复实验的结果,过滤阵列中有问题的区域,并评估单个实验和重复实验的质量。ExpressYourself采用高度模块化的架构设计,因此随着各种微阵列分析算法的开发,可以很容易地将它们纳入;例如,该系统目前实现了几种归一化方法,包括那些同时考虑信号强度和载玻片位置的方法。处理后的数据通过基于网络的图形界面呈现,便于与阵列载玻片的原始图像进行比较。特别是,Express Yourself能够在应用各种处理步骤后重新生成原始微阵列的图像,这极大地有助于识别位置特异性伪像。该程序可在http://bioinfo.mbb.yale.edu/expressyourself免费使用。