Better protocols and decreasing costs have made high-throughput sequencing experiments now accessible even to small experimental laboratories. However, comparing one or few experiments generated by an individual lab to the vast amount of relevant data freely available in the public domain might be limited due to lack of bioinformatics expertise. Though several tools, including genome browsers, allow such comparison at a single gene level, they do not provide a genome-wide view.
University of Edinburgh researchers have developed Heat*seq, a web-tool that allows genome scale comparison of high throughput experiments (ChIP-seq, RNA-seq and CAGE) provided by a user, to the data in the public domain. Heat*seq currently contains over 12,000 experiments across diverse tissues and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualise user experiments. High quality figures and tables are produced and can be downloaded in multiple formats.
Correlations heatmaps from Heat*seq
A. ERα ChIP-seq in MCF7 cells from Zhuang et al. is closer to ENCODE ERα ChIP-seq in T-47D than in ECC-1 cells. B. BRF1 and RNA PolIII bind tRNA genes, but nor BRF2. C. c-MYC ChIP-seq in H1-hESC from UT-A and Stanford show low correlation. The color key next to B is for A, B and C. D. Two erythroblast RNA-seq samples from BLUEPRINT are closely related to endothelial cells.