October 30, 2015 @ 11:00 am – 12:00 pm
Room 6115, Lane Center for Computational Biology (CMU)
Entrance To Gates Hillman Center
5000 Forbes Ave, Pittsburgh, PA 15213

Ben Raphael, PhD, Brown University

Advances in DNA sequencing technology have enabled large-scale measurement of the molecular alterations that occur in cancer cells. Translating this information into deeper insights about processes that drive cancer development demands novel computational approaches.

In this talk, I will describe algorithms to address two key problems in cancer genomics. First, I will describe techniques to identify combinations of mutations that perturb cellular signaling and regulatory networks. One algorithm employs a heat diffusion process to identify subnetworks of a genome-scale interaction network that are recurrently altered across samples. A second algorithm finds combinations of mutations that optimize a statistical measure of mutual exclusivity. Next, I will discuss approaches to deconvolve DNA sequencing data from bulk tumor samples and to derive a phylogenetic tree that relates subpopulations of tumor cells within these samples. I will illustrate applications of these approaches to multiple cancer types in The Cancer Genome Atlas (TCGA), including a recent Pan-Cancer study of >3000 samples from 12 cancer types.