摘要
目的比较基因芯片数据分析中常用的用于筛选差异表达基因的几种方法,探讨各方法的筛选效果。方法使用Bonferroni修正法等8种保守的方法以及两样本t检验、Wilcoxon非参数法、SAM共11种方法对模拟的芯片数据进行处理,以FDR(False discovery rate)和筛检的差异表达基因个数为指标考察其筛选效果。结果SAM的FDR仅次于8种保守的方法,但筛检的差异表达基因个数较多,适合基因芯片初筛差异表达基因的目的。结论SAM适合基因芯片初筛差异表达基因的目的。
Objective To compare the performance of methods used in the microarray data analysis for selecting differentially expressed genes. Methods 8 conservative methods including Bonferroni adjustment and 7 others, two sample t test, Wilcoxon approach and SAM approach, all together 11 methods are used to analyze the simulated data. FDR （False discovery rate） and the number of detected differentially expressed genes are employed to evaluate these methods. Results The FDR of SAM is second only to the 8 conservative methods, yet it detects more genes which are differentially expressed. Therefore the SAM approach may be more suitable for the purpose of microarray to select differentially expressed genes. Conclusion SAM is suitable for the purpose of microarray to screen the differentially expressed genes.
出处
《中国卫生统计》
CSCD
北大核心
2006年第5期417-420,共4页
Chinese Journal of Health Statistics
关键词
差异表达基因
模拟数据
FDR
Differentially expressed genes, Simulated data, FDR
