Cytogenetic abnormalities, such as DNA amplifications and deletions, often lead to significant changes in gene expression levels within a chromosomal region. Instead of generating additional DNA copy number data, one method to identify DNA copy number abnormalities has been to search existing gene expression data for regional perturbations in gene expression. However, it is not clear how well this surrogate method performs in the examination of individual tumors and how we can use both DNA and RNA data to identify candidate genes that may be mutated. Here we report a comparison study using summarized DNA and RNA data to identify chromosomal abnormalities in human samples. Forty-four tissue samples from patients diagnosed as having renal cell carcinoma (RCC) were collected, together with 15 normal kidney samples as controls, and for each sample the genome-wide DNA and RNA data were obtained for comparison using Affymetrix 100K SNP and HGU133plus2 gene expression chips, respectively. The DNA and RNA data was summarized by both chromosome arm and cytogenetic banding patterns and compared. The result of this analysis revealed that the two summarized data sets used to identify cytogenetic changes agreed well. However, some differences between the two were also identified. These differences of large-scale gene expression deregulation without evidence of the comparable DNA copy number alterations may be the result of known mechanisms, such as large-scale methylation or chromosome inactivation, or may be the result of some new mechanism of DNA-RNA translation. The usefulness of the combined data set for identifying regions of mutated genes is also discussed.