GRIDLINE: AUTOMATIC GRID ALIGNMENT IN DNA MICROARRAY SCANS

Peter Bajcsy, National Center for Supercomputing Applications

IEEE Transactions on Image Processing 13 p15-25 (2004)

We present a new automatic grid alignment algorithm for detecting two-dimensional (2D) arrays of spots in DNA microarray images. Our motivation for this work is the lack of automation in high-throughput microarray data analysis that leads to (a) spatial inaccuracy of located spots and hence inaccuracy of extracted information from a spot, and (b) inconsistency of extracted features due to manual selection of grid alignment parameters. The proposed grid alignment algorithm is novel in the sense that (1) it can detect irregularly row- and columnspaced spots in a 2D array, (2) it is independent of spot color and size, (3) it is general to localize a grid of other primitive shapes than the spot shapes, (4) it can perform grid alignment on any number of input channels, (5) it reduces the number of free parameters to minimum by data driven optimization of most algorithmic parameters and (6) it has a built-in speed versus accuracy tradeoff mechanism to accommodate user's requirements on performance time and accuracy of the results. The developed algorithm also automatically identifies multiple blocks of 2D arrays, as it is the case in microarray images, and compensates for grid rotations in addition to grid translations.

Key words: DNA microarray, spot alignment, image analysis, simulation, and quality control.