cDNA microarray是近年來生物技術上研發出來的新方法，它能同時得到數千個基因表現值。但在Microarray的實驗過程中，無可避免地會產生系統性變異。在分析資料前必須先經過Normalization，以移除系統變異，否則將產生不良的影響。現階段已存在的normalization法各有其假設，因此不同的normalization依假設之滿足與否各有其績效。本研究的目的在比較median法、lowess法、block lowess法和spatial法的差異，並藉由模擬來了解normalization方法的表現及其適用情形。我們以百恩諾公司的microarray資料為例來說明各normalization法的應用。

The cDNA microarray which can obtain thousands of gene expressions simultaneously is a new method in biotechnology developed in recent years. System variations usually occur during the process of microarray experiment, which result in wrong results in downstream analysis. In order to remove the systematic bias, normalization is necessary before analysing the microarray data. Each of the normalization method has each own assumptions, so the performance of normalization method relies on whether the assumptions are satisfied. The purpose of the study is to compare the performance of median method, lowess method, block lowess method and spatial method. Through simulation, we found the advantage of one normalization method is over another if the required assumption is satisfied. We use a microarray data from ABC Company to illustrate the simulation findings for different normalization methods.

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