Single-nucleotide polymorphism (SNP) mapping arrays are a reliable method for identifying somatic copy number alterations in cancer samples. Though this is immensely useful to identify potential driver genes, it is not sufficient to identify genes acting in a concerted manner. In cancer cells, co-amplified genes have been shown to provide synergistic effects, and genomic alterations targeting a pathway have been shown to occur in a mutually exclusive manner. We therefore developed a bioinformatic method for detecting such gene pairs using an integrated analysis of genomic copy number and gene expression data. This approach allowed us to identify a gene pair that is co-amplified and co-expressed in high-grade serous ovarian cancer. This finding provided information about the interaction of specific genetic events that contribute to the development and progression of this disease.