New tool to better analyse human genomic data

Researchers have developed a new, web-based tool that enables them to quickly and easily visualise and compare large amounts of genomic information resulting from high-throughput sequencing experiments.
To visualise and browse entire genomes, graphical interfaces that display information from a database of genomic data - called "genome browsers" - have been created.
The new tool, named Epiviz, developed at the University of Maryland, offers a major advantage over browsers currently available: Epiviz integrates with the open-source Bioconductor analysis software widely used by genomic scientists.
Since Epiviz is based on the Bioconductor infrastructure, the tool supports many popular next-generation sequencing techniques, such as ChIP-seq, which is used to analyse protein interactions with DNA; RNA-seq, which reveals a comprehensive snapshot of the abundance of RNAs in cells; and DNA methylation analyses.

Epiviz implements multiple visualisation methods for location-based data (such as genomic regions of interest) and feature-based data (such as gene expression), using interactive data visualisation techniques not available in web-based genome browsers.
For example, because display objects are mapped directly to data elements, Epiviz links data across different visualisations giving users visual insights of the spatial relationships of multiple data sets.

The tool is designed to allow biomedical scientists to easily incorporate their own visualisations.
In a paper published in the journal Nature Methods, researchers used Epiviz to visualise and analyse DNA methylation and gene expression data in colon cancer.

Changes in DNA methylation patterns compared with normal tissue have been associated with a large number of human malignancies.
Using Epiviz and Bioconductor, the research team found consistent regions of DNA methylation changes in colon cancer samples generated by the public Cancer Genome Atlas project and similar gene expression in these regions of DNA methylation changes in other cancer types.
The results were in agreement with previous experiments, which were conducted by researchers at Johns Hopkins University, showing DNA methylation changes across large regions in the colon cancer genome.