Completion of the Human Genome Working Draft has made it possible to analyze the expression profiles of genes according to their position on the genome. Using transcriptome data from 130 invasive ductal breast carcinomas, the authors constructed a genome-wide transcriptome correlation map highlighting neighboring genes with correlated expression profiles. These genes are grouped into clusters, many of which correspond to known amplicons or chromosomal regions of gains or losses. Other clusters may be related to different events such as epigenetic regulation. Upper panel, the transcriptome correlation map of 130 breast carcinomas for chromosome 17. Lower panel, an unsupervised hierarchical cluster analysis of the genes with a significant transcriptome correlation score (TC score) on the long arm of chromosome 17. Transcriptome correlation maps are a new way of interpreting transcriptome data that will help to identify genes involved in tumor progression. For details, see the article by Reyal, Stransky, Bernard-Pierrot et al. on page 1376 of this issue.