Abstract
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 10,368 genes using edge detection and compared the result with that of conventional method which draws circle around the spot.
Highlights
As the human genome project has nearly been completed, the attention is being focused on understanding the gene expression profiling of disease state of cells and tissues as well as the development of platform technology or methodology for detecting and quantitating gene expression levels utilizing Northern blots, S1 nuclease protection, differential display, sequencing of cDNA libraries, and serial analysis of gene expression (SAGE) analysis
In the case of cDNA microarray, cDNA amplified from IMAGE, cDNA clone set, or a custom cDNA library are usually spotted on the glass at high density
We have developed an efficient image-processing package for the use with cDNA microarrays, and in this report we demonstrated the new technology of microarray image analysis
Summary
As the human genome project has nearly been completed, the attention is being focused on understanding the gene expression profiling of disease state of cells and tissues as well as the development of platform technology or methodology for detecting and quantitating gene expression levels utilizing Northern blots, S1 nuclease protection, differential display, sequencing of cDNA libraries, and SAGE analysis. These methods are augmented by two microarray-based technologies – i.e. cDNA and oligonucleotide arrays (Duggan et al, 1999). It is important to choose a weak background noise as a support of microarray chip, because a strong background noise increases the SNR and it is hard to isolate the spots from the noise
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