Abstract
DNA copy number aberrations along the genome are vital markers for studying pathogenesis of various diseases including cancers. Array-based Comparative Genome Hybridization (aCGH), which is a high-throughput cytogenetic method, helps in identifying genome-wide copy number aberrations, both gains and losses. Here, we propose a computational technique to analyze aCGH data and to identify potential DNA copy number alterations along the genome. Our technique detects the possible breakpoints by comparing contiguous probe log ratios, reports the aberrant segments and handles outliers to minimize false discovery rate. Empirically, we tested our algorithm on both prokaryotic (Brucella ovis) and eukaryotic (glioblastoma and colorectal cancer datasets from human) genomes. Our findings complement previous studies; our performance is competitive, sometimes superior, against other popular methods.