GLEAMS: a novel approach to high-throughput genetic microarray image capture and analysis

GLEAMS is a robust, stable and accurate image capture and quantification method for microarrays. It is capable of fully and automatically detecting and quantifying the expression spots. This can be done in a batch mode, without human intervention, achieving a high throughput of parallel data processing. Simple to use visual tools are provided to estimate parameters and to submit, monitor and control jobs execution. The un-supervised batch auto-alignment is based on a novel method requiring only knowledge of the number of rows and columns of dots in the array. Distances between dots along rows and columns are estimated from the image's auto- correlation function. This is also used to align the array and the sides of the image. Applying intensity and geometric constraints to the cross-correlation function between the image and a template sub-array, the location of the sub-arrays can be determined. Carefully implemented, the algorithm can approach human vision in its sensitivity and accuracy in finding the general positions of dots in a micro-array image. Subsequent spot quantification uses Ostu's thresholding method followed by some morphological operations, including the application of a constraining shape mask. Segmentation techniques are applied to detect and remove speckles from the targets and to ensure the veracity of the data extracted.