Identifying spots in microarray images

Abstract

Microarray technology has provided a way to quantitate the simultaneous expression of a large number of genes. This approach is dependent on reproducible, accurate identification and quantitation of spot intensities. In this paper, clustering-based image segmentation is described to extract the target intensity of the microarray spots. While the technique is generic, its effectiveness on extracting spot intensities on arrays obtained from a two-color (Cy3/Cy5) experiment is discussed. The approximate boundaries of the spots are determined initially by manual alignment of rectangular grids. The pixel intensities of the image (I) inside a grid, is mapped onto a one-dimensional vector (v). The k-means clustering technique is applied to generate a binary partition of v. The median value of the pixel intensities inside each of the clusters for a given spot determines its foreground and the local background intensity. The difference in the median value of the foreground and the background intensity is the desired target intensity of the spot. The results are compared against those obtained using a region growing approach.