Introduction

Array Comparative Genome Hybridization (array CGH) (Pinkel et al., 1998; Solinas-Toldo et al., 1997) requires sophisticated statistical methods for analyzing the sample versus reference signal ratios and extracting the loss and gain regions in a reproducible way, as robust and powerful as possible. Once a microarray has been constructed, hybridization carried out and image of the array scanned, three essential steps must be completed to extract the meaningful biological information out of the arrays : (1) array normalization, (2) breakpoint detection and (3) assignment of a status (gain/loss/normal) to all regions defined by the breakpoints. Here we present the algorithms GLAD that have been designed to carry out the last two steps.