Cancer is caused by genomic alterations that disrupt normal cell function related to the regulation of DNA repair, genome stability, cell proliferation, cell death, adhesion, angiogenesis, invasion, and metastasis. These aberrations can be naturally caused by changes in genome copy number (through amplication, deletion, chromosome loss, or duplication), changes in gene and chromosome structure, gene expression, and point mutations. In this work, I demonstrate an approach using High Performance Computing to analyze large amounts of data related to gene expression and copy number in tumor samples and describe an algorithm that extends GISTIC to filter genes help to identify candidate "driver" alterations in cancer. The new algorithm reduces the genomic regions of interest that GISTIC identifies and contains virtually the same set of oncogenes as has been identified in the literature by TCGA Gene Rank Lists.

See the write-up for this project.