We have developed computational approaches to detect copy-number alterations and rearrangements from high-throughput sequencing data, to distinguish positively selected from passenger events, and to determine functionally relevant associations between genetic events. We have applied these approaches to genomic data representing tens of thousands of cancers, determining mechanistic and selective forces shaping the cancer genome.
Developing computational approaches to interpret cancer genomes | Comprehensive genomic characterization of brain cancers
