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本文的目的是对MA小鼠左、右脑的多元三维脑基因表达图谱的基因芯片数据进行相关分析。首先,我们从原始数据中筛选出有效数据并用log ratio作为我们分析的对象。然后,计算相关系数,找到基因与基因表达水平之间的相关信息。最后,分类和层次聚类能帮我们找到帕金森氏病的相关基因。通过这个统计学方法我们发现了变异小脑的基因不对称性,这将对在未来的实验中研究帕金森氏病是很有帮助的。
The purpose of this paper is to analyze the gene chip data of multivariate three-dimensional brain gene expression profiles of left and right brains of MA mice. First, we filter out the valid data from the raw data and use log ratio as our analysis object. Then, calculate the correlation coefficient to find the relevant information between gene and gene expression level. Finally, the classification and hierarchical clustering can help us to find the related genes of Parkinson’s disease. Through this statistical method, we discovered the genetic asymmetry of the mutant cerebellum, which will be very helpful in the study of Parkinson’s disease in future experiments.