Wen Chi-Chung, Wu Yuh-Jenn, Huang Yung-Hsiang, Chen Wei-Chen, Liu Shu-Chen, Jiang Shih Sheng, Juang Jyh-Lyh, Lin Chung-Yen, Fang Wen-Tsen, Hsiung Chao Agnes, Chang I-Shou
National Health Research Institutes, Taiwan.
Stat Appl Genet Mol Biol. 2006;5:Article3. doi: 10.2202/1544-6115.1149. Epub 2006 Feb 16.
This paper develops a Bayes regression model having change points for the analysis of array-CGH data by utilizing not only the underlying spatial structure of the genomic alterations but also the observation that the noise associated with the ratio of the fluorescence intensities is bigger when the intensities get smaller. We show that this Bayes regression approach is particularly suitable for the analysis of cDNA microarray-CGH data, which are generally noisier than those using genomic clones. A simulation study and a real data analysis are included to illustrate this approach.
本文通过不仅利用基因组改变的潜在空间结构，还利用当荧光强度变小时与荧光强度比值相关的噪声更大这一观察结果，开发了一种具有变化点的贝叶斯回归模型，用于分析阵列比较基因组杂交（array-CGH）数据。我们表明，这种贝叶斯回归方法特别适用于分析互补DNA微阵列比较基因组杂交（cDNA microarray-CGH）数据，这类数据通常比使用基因组克隆的数据噪声更大。文中包含了一个模拟研究和一个实际数据分析来阐述这种方法。
