DNA拷貝數（CN）和RNA表達之間的關聯是癌症研究中的重要問題。具有強DNA-RNA結合的關鍵基因可以作為治療靶標。在這項研究中，我們探索了幾種方法來識別特定癌症患者群體中具有強DNA-RNA關聯的基因。我們分析了從Genomic Data Commons（GDC）下載的結腸腺癌（COAD）患者。我們使用工具集'Bedtools'和註釋'非重疊GRCh38'來建立一個新的計算讀數計數方法。新計算的讀數計數方法是解決不同轉錄本的外顯子可能重疊的問題。在獲得讀數後，我們使用最大信息係數（MIC），距離相關（dCor）和多變量自適應回歸樣條（MARS）來找出DNA拷貝數表達與RNA表達之間的二維關聯。本研究中的創新算法稱為A2dMIC，它能夠計算DNA拷貝數表達與基因間RNA表達之間的三維關聯。

The association between DNA Copy Number (CN) and RNA expressions is an important issue in cancer studies. The critical genes with strong DNA-RNA association may serve as therapeutic targets. In this study, we explore several methods to identify genes with strong DNA-RNA association in specific groups of cancer patients. We analyze the patients with the Colon Adenocarcinoma (COAD) downloaded from the Genomic Data Commons (GDC). We used the toolset 'Bedtools” and the annotation 'non-overlap GRCh38” to establish a new calculation read count method. The new calculated read count method is to solve the problem that the exons of the different transcripts may be overlapping. After obtaining the read counts, we using maximal information coefficient (MIC), distance correlation (dCor) and Multivariate Adaptive Regression Splines (MARS) to find out the two-dimensional association between DNA copy number expression and RNA expressions. And the innovative algorithm in this study is called A2dMIC, which is able to calculate the three-dimensional association between the DNA copy number expression and RNA expressions across genes.

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