Furusawa Chikara, Ono Naoaki, Suzuki Shingo, Agata Tomoharu, Shimizu Hiroshi, Yomo Tetsuya
Department of Bioinformatics Engineering, Graduate School of Information Science and Technology, Osaka University, Suita, Osaka 565-0871, Japan.
Bioinformatics. 2009 Jan 1;25(1):36-41. doi: 10.1093/bioinformatics/btn570. Epub 2008 Oct 31.
High-density DNA microarrays provide us with useful tools for analyzing DNA and RNA comprehensively. However, the background signal caused by the non-specific binding (NSB) between probe and target makes it difficult to obtain accurate measurements. To remove the background signal, there is a set of background probes on Affymetrix Exon arrays to represent the amount of non-specific signals, and an accurate estimation of non-specific signals using these background probes is desirable for improvement of microarray analyses.
We developed a thermodynamic model of NSB on short nucleotide microarrays in which the NSBs are modeled by duplex formation of probes and multiple hypothetical targets. We fitted the observed signal intensities of the background probes with those expected by the model to obtain the model parameters. As a result, we found that the presented model can improve the accuracy of prediction of non-specific signals in comparison with previously proposed methods. This result will provide a useful method to correct for the background signal in oligonucleotide microarray analysis.
The software is implemented in the R language and can be downloaded from our website (http://www-shimizu.ist.osaka-u.ac.jp/shimizu_lab/MSNS/).
高密度DNA微阵列给我们提供了全面分析DNA和RNA的有用工具。然而，探针与靶标之间的非特异性结合（NSB）所导致的背景信号使得难以获得准确的测量结果。为了去除背景信号，Affymetrix外显子阵列上有一组背景探针来代表非特异性信号的量，并且使用这些背景探针准确估计非特异性信号对于改进微阵列分析是很有必要的。
我们开发了一种短核苷酸微阵列上NSB的热力学模型，其中NSB通过探针与多个假设靶标的双链体形成来建模。我们将背景探针的观察信号强度与模型预期的信号强度进行拟合以获得模型参数。结果，我们发现与先前提出的方法相比，所提出的模型可以提高非特异性信号预测的准确性。这一结果将为校正寡核苷酸微阵列分析中的背景信号提供一种有用的方法。
该软件用R语言实现，可从我们的网站（http://www-shimizu.ist.osaka-u.ac.jp/shimizu_lab/MSNS/）下载。
