Automation of cDNA microarray image analysisJin Hyuk Kim1, Hye Young Kim2, Tae Sung Park, Ki Woong Kim, Young Seek Lee, and Yong Sung Lee
firstname.lastname@example.org, Hanyang Univeirsity College of Medicine; email@example.com, Hanyang University College of Medicine
cDNA microarray experiments enable us to find out the genes whose expressions are changed by the internal or external stimulation on the cells. The accuracy of cDNA microarray technology has been improved and the frequency of microarray experiments in life science researches has grown rapidly. Large increase can be expected in the production of cDNA microarray images. Therefore, it is necessary to make the analysis of them automatic. Several factors are critical in the automation of microarray image analysis. One of them is to locate the spots in the image and another is to qualify them automatically. In order to locate the spots in the image, the novel preprocessing algorithm was devised for clarifying the spots and several steps were included to correct the errors in finding spots. Generally, a few measures based on the spotís intensities have been used for qualifying them. However, they are insufficient to filtering out the bad spots without the visual confirmation. Because some filters are needed to decrease the possibility missing the bad spots, some measures based on the spot shape are developed. All of these procedures included in the microarray image analysis software can produce the data successfully without userís attention and it can also generate the HTML format report. Batch process can analyze a lot of cDNA microarray images at once. It can be a connection in high throughput pipeline.