A Markov Random Field model of microarray gridding
Proceedings of the 2003 ACM symposium on Applied computing
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Image and statistical analysis are two important aspects of microarray technology. Of these, gridding is necessary to accurately identify the location of each spot while extracting spot intensities from the microarray images and automating this procedure permits high-throughput analysis. In this paper, an automatic gridding and spot quantification technique is proposed, which takes a microarray image (or a sub-grid) as input, and makes no assumptions about the size of the spots, and number of rows and columns in the grid. The proposed method is based on a weighted energy maximization algorithm that utilizes three different energy functions. The method has been found to effectively detect the grids on microarray images drawn from databases from GEO, Stanford genomic laboratories and on some images obtained from private repositories.