This paper is aimed to predict Parkinson disease (PD) genes from multiplex Three-Dimensional brain gene expression mapping. First, we select the available data from the original datasets and use log ratio as the object that we would analysis. Second, correlation coefficient calculated provides information on the correlation between genes based on gene expression levels. Later, classification and hierarchical cluster analysis can help us to find the relevant genes of Parkinson disease. The 27 genes selected by the statistical method are worthy of further experiments to assess the results of microarray.
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