在cDNA微陣列實驗裡，最重要且普遍的問題即是在不同樣本間，搜尋有哪些基因具有表現量的差異。一般皆利用統計方法去對所有基因作多重假設檢定分析，然而在真實微陣列資料裡，檢定統計量往往不符合一般常見的分配，如常態分配、t分配、F分配等等，導致錯誤拒絕率無法有效控制，因而產生過多的錯誤拒絕。文本藉由有內部控制的實驗設計，透過兩個相同的樣本去製造檢定時的虛無假設分配，提供更精確的分析。

Benjamini, Y. and Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society B 57, 289-300

Cui, X. and Churchill, G.A. (2003). Statistical tests for differential expression in cDNA microarray experiments. Genome Biology, Vol. 4, Issue 4, 210.1-210.10.

Efron, B., Tibshirani, R., Storey, J.D., and Tusher, V. (2001). Empirical Bayes analysis of a microarray experiment. Journal of the American Statistical Association 96, 1151-1160

Hochberg, Y. (1988). A Sharper Bonferroni Procedure for Multiple Tests of Significance. Biometrike, Vol. 75, No. 4, 800-802

Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics: Theory and Applications 6, 65-70

Ideler, T., Thorsson, V., Siegel, A.F., and Hood, L.E. (2000). Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data. Journal of Computational Biology 7, 805-817

Kerr, M.K., Martin, M., and Churchill, G.A. (2000). Analysis of variance for gene expression microarray data. Journal of Computational Biology 7, 819-837

Rao, C.R. and Toutenburg, H. (1999). Linear Model. Springer, New York

Schena, M., Shaon, D., Heller, R., Chai, A., Brown, P., and Davis, R.W. (1996). Parallel human genome analysis: microarray-based expression monitoring of 1000 genes. Proceedings of the National Academy of Sciences USA 93, 10614-10619.

Storey, J.D. and Tibshirani, R. (2003b). Statistical significance for genome-wide studies. Proceedings of the National Academy of Sciences USA 100, 9440-9445.

Tusher, V.G., Tibshirani, R., and Chu, G. (2001). Significance analysis of microarrays applied to the ionizing radiation response. Prodeedings of the National Academy of Sciences USA 98, 5116-5121.

Westfall, P.H. and Young, S.S. (1993). Resampling Based Multiple Testing: Examples and Methods for p-Value Adjustment. New York: Wiley.

Yang, Y.H., Dudoit, S., Luu, P., Lin, D.M., Peng, V., Ngai, J., and Speed, T.P. (2002b). Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Research 30, e15.

王陽照 (2003)，cDNA微陣列的實驗設計與數據分析，國立清華大學統計學研究所碩士論文。