Abstract: | Microarray experiment enables us to record the expression levels of thousands of genes at one time and identify differentially expressed genes(DEGs). Microarray technology involves many steps and for each step there may introduce background noises, so an effective way of identifying DEGs from microarray becomes very important. The R is a kind of integrated data processing and statistical software, and the Bioconductor is a R-based application software of analying genomic information that can be used to analyze microarray data. In this study, the R and Bioconductor are used to screen and analyze DEGs of microarray of prostate cancer data. By integrating the Tumor Associated Gene (TAG), ncRNAppi and miR2Disease databases, it is found that certain DEGs are regulated by microRNAs. The findings are as follows: (1) the adjusted p-values of the top 100 DEGs are less than 5 1.9 10 , and there are 16 cancer-related genes among the top 100 DEGs, (2) three genes, FOS, AXL and TGFBR2, are regulated by the microRNA miR-101, miR-1 and miR-20a, respectively, and two genes, the PLP2 and CD59, are regulated by the microRNA miR-124, and GJA1, is regulated by both miR-206 and miR-1, (3) miR-101 is related with six types of cancers, including prostate cancer, and miR-1 is related with four types of cancers, and the miR-20a is related with eight types of cancers, including prostate cancer, and the miR-124 is related with one type of cancer, and the miR-206 is related with two types of cancers, and (4) TGFBR2 is regulated by miR-20a inducing prostate cancer. The web site of studying results is available at http://ppi.bioinfo.asia.edu.tw/R_prostate_cancer/index.htm. |