| 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. |
