The overarching goal of the Computational Core is to provide robust and reproducible analysis of high- throughput genomic (WES), epigenomic (ChIP-seq, ATAC-seq, WGBS and RRBS), chromatin conformation (Hi-C and 4C) and transcriptomic (RNA-seq and single-cell RNA-seq) data using a variety of established computational workflows, methods and tools. All genomics data will be uniformly processed by HiC-bench, our recently published computational platform. The Computational Core will provide start-to-finish standardization of the analysis of sequencing datasets, rigorous data quality assessment, integration and visualization, as well as statistical expertise. The results of the bioinformatics analyses conducted in the Core will be utilized by all three Projects, using the sharable workflows of our computational platform. Finally, the bioinformatics staff will setup a web interface for the data and analyses, accessible to all members of the proposed study. This web interface will also facilitate data sharing with the broader scientific community and the public when our studies are published.
The dramatic decrease in the cost of high-throughput genomics technologies has rapidly expanded our understanding of the molecular underpinnings of cancer. However, as the scale of such data increases and become more diverse, data management, computational analysis and interpretation can be the major bottle- neck. The Computational Core will not only provide robust and reproducible analysis of high-throughput genetic, epigenetic, chromatin conformation and transcriptomic data, but, will also utilize data integration techniques to help elucidate the role of chromatin architecture in tumor initiation and progression.
