選擇性剪接（alternative splicing）是以酵素從DNA主要轉錄物mRNA前體經過剪接作用，移去內含子（intron）形成mRNA的處理過程。但在移去插入序列時，有時外顯子（exon）會一起移去，也有時內含子沒有被移去，造成基因微晶片實驗偵測不出致病基因，因而使用外顯子晶片（exon array）來偵測致病基因。透過選擇性剪接，一個基因會有多種異構物，因此偵測致病基因和估計不同的異構物是現今重要課題之一。文中使用Affymetrix GeneChip Human Exon 1.0 ST Arrays，以十位結腸癌病人之腫瘤組織和正常組織配對樣本為例，使用Wilcoxon signed-rank檢定挑選出可能影響疾病的基因，若顯著水準為5%，可從312,368個transcript clusters中挑選出54,854個疑似致病transcript clusters。在這些疑似致病transcript clusters下，分別利用t檢定和因素分析二方法估計正常與患有結腸癌基因的異構物型態。最後，將分析結果與Alternative Splicing Database（ASD）進行比對。本文提出和過去不同的分析方法，結果可提供給生物學家進行生物實驗確認並發現致病異構物型態。

Alternative splicing is the RNA splicing variation mechanism. The exon isoforms lead to numerous different expressions through the alternative splicing. It’s imperative to find the diseased gene from the massive quantity of genes and understand the ex-pressed isoforms. In this paper, the statistical procedures are applied on the colon can-cer sample data of Affymetrix GeneChip Human Exon 1.0 ST Array as an example of finding isoforms. First, we apply the Wilcoxon signed-rank test to choose the influen-tial genes. About 54,854 transcript clusters are selected from original 312,368 tran-script clusters at 5% significant level. Second, one sample t-test and the factor analy-sis are used to estimate the tumor and normal isoforms for each transcript cluster, re-spectively. Furthermore, the confirmations are made by comparing the estimated re-sults with Alternative Splicing Database (ASD). Finally, the results may be provided to the biologist to make biological confirmations and discover the new isoforms.

[1] Affymetrix White Paper, (2005) Alternative transcript analysis methods for exon arrays.
http://www.affymetrix.com/support/technical/whitepapers/exon_alt_transcript_analysis_whitepaper.pdf

[2] Alternative Splicing Database. (2008, June)
http://www.ebi.ac.uk/asd/

[3] Brett, D., Hanke, J., Lehmann, G., Haase, S., Krueger, S., Reich, J. and Bork, P. (2000) EST comparison indicates 38% of human mRNAs contain possible alternative splicing form. FEBS Letters, 474, 83-86.

[4] Ceres, J. F. and Kornblihtt, A. R. (2002) Alternative splicing: multiple control mechanisms and involvement in human disease. Trends in Genetics, 18, 186-193.

[5] Cline, M. S., Blume, J., Cawley, S., Clark, T. A., Hu, J. S., Lu, G., Salomonis, N., Wang, H. and Williams, A. (2005) ANOSVA: A statistical method for detect-ing splice variation from expression data. Bioinformatics, 21, i107-i115.

[6] Gardina, P. J., Clark, T. A., Shimada, B., Staples, M. K., Yang, Q., Veitch, J., Schweitzer, A., Awad, T., Sugnet, C., Dee, S., Davies, C., Williams, A. and Tur-paz, Y. (2006) Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array. BMC Genomics, 7, 325.

[7] Johnson, J. M., Castle, J., Garrett-Engele, P., Kan, Z., Loerch, P. M., Armour, C, D,, Santos, R., Schadt, E. E., Stoughton, R. and Shoemaker, D. D. (2003) Ge-nome-wide survey of human alternative pre-mRNA splicing with exon junc-tion microarrays. Science, 302, 2141-2144.

[8] Yoshida, R., Numata, K., Imoto, S., Nagasaki, M., Doi, A., Ueno, K. and Miyano, S. (2006) A statistical framework for genome-wide discovery of biomarker splice variations with GeneChip Human Exon 1.0 ST arrays. Genome Infor-matics, 17, 88-100.