Kim Seo Young, Lee Jae Won, Sohn In Suk
Research Institute for Basic Science, Chonnam National University, Gwangju, Korea.
Stat Methods Med Res. 2006 Feb;15(1):3-20. doi: 10.1191/0962280206sm423oa.
DNA microarray is a new tool in biotechnology, which allows the simultaneous monitoring of thousands of gene expression in cells. The goal of differential gene expression analysis is to identify those genes whose expression levels change significantly by the experimental conditions. Although various statistical methods have been suggested to confirm differential gene expression, only a few studies compared the performance of the statistical tests. In our study, we extensively compared three types of parametric methods such as T-test, B-statistic and Bayes T-test and three types of non-parametric methods such as samroc, significance analysis of microarray and a modified mixture model using both the simulated datasets and the three real microarray experiments.
DNA微阵列是生物技术中的一种新工具，它能够同时监测细胞中数千个基因的表达。差异基因表达分析的目的是识别那些在实验条件下表达水平发生显著变化的基因。尽管已经提出了各种统计方法来确认差异基因表达，但只有少数研究比较了这些统计检验的性能。在我们的研究中，我们广泛比较了三种参数方法，如T检验、B统计量和贝叶斯T检验，以及三种非参数方法，如samroc、微阵列显著性分析和一种使用模拟数据集和三个真实微阵列实验的改进混合模型。
