Abstract
Motivation: The analysis of high-throughput experiment data provided by microarrays becomes increasingly more and more important part of modern biological science. Microarrays allow to conduct genotyping or gene expression experiments on hundreds of thousands of test genes in parallel. Because of the large and constantly growing amount of experimental data the necessity of efficiency, robustness and complete automation of microarray image analysis algorithms is gaining significant attention in the field of microarray processing. Results: The author presents here an efficient and completely automatic image registration algorithm (that is an algorithm for spots and blocks indexing) that allows to process a wide variety of microarray slides with different parameters of grid and block spacing as well as spot sizes. The algorithm scales linearly with the grid size, the time complexity is O(M), where M is number of rows × number of columns. It can successfully cope with local and global distortions of the grid, such as focal distortions and non-orthogonal transformations. The algorithm has been tested both on CCD and scanned images and showed very good performance—the processing time of a single slide with 44 blocks of 200 × 200 grid points (or 1 760 000 grid points total) was about 10 s. Availability: The test implementation of the algorithm will be available upon request for academics. Supplementary information:http://fleece.ucsd.edu/~vit/Registration_Supplement.pdf

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