检测cDNA芯片中差异表达基因的非转换方法

cDNA芯片已经成为生物学试验中一种重要试验手段,与其相应的检测差异表达基因的统计方法也在快速地完善。目前通用的方法是将数据进行对数比转换,并相应进行标准化处理。鉴于对数转换的缺点,本研究提出一种非转换方法,即背景校正后直接进行数据标准化。研究表明:利用这种非转换方法,可以更有效地剔除试验中的“噪音,”提高检测的准确率。本研究利用Apo AI试验的芯片数据进行了效率验证,结果表明:与对数转换方法相比,非转换方法能检测出更多的差异表达基因,可以作为cDNA芯片数据分析的一种简便高效方法。

A Non-transformation Method for Detecting Differentially Expressed Genes Using cDNA Microarray

cDNA microarrays have been standard equipments in biology laboratories.Methods for identifying differentially expressed genes are still evolving.The currently widely used method involves log-transformation,and normalization of the measured intensities before the statistical testing for the differentially expressed genes.A method proposed in this paper avoids the log-transformation in view of its drawbacks,specially the log-ratio transformation,but normalizes the data after background correction.This method could better estimate the "noise" effect by utilizing the information more effectively and improve the identification power.cDNA microarray data in the Apo AI experiment were analyzed to test the feasibility and efficiency of this approach for detecting differentially expressed genes.The results showed that this method can identify more genes than log-transformation method.Therefore,it could be an alternative method for analyzing cDNA microarray data.