A novel method using edge detection for signal extraction from cDNA microarray image analysis

Gene expression analyses by probes of hybridization from mRNA to cDNA targets arrayed on membranes or activated glass surfaces have revolutionized the way of profiling mega level gene expression. The main remaining problems however are sensitivity of detection, reproducibility and data processing. During processing of microarray images, especially irregularities of spot position and shape could generate significant errors: small regions of signal spots can be mis-included into background area and vice versa. Here we report a novel method to eliminate such obstacles by sensing their edges. Application of edge detection technology on separating spots from the background decreases the probability of the errors and gives more accurate information about the states of spots such as the pixel number, degree of fragmentation, width and height of spot, and circumference of spot. Such information can be used for the quality control of cDNA microarray experiments and filtering of low quality spots. We analyzed the cDNA microarray image that contains 10,358 genes using edge detection and compared the result with that of conventional method which draws circle around the spot.