“Integrative computational models for functional interpretation of human genomic sequence variants’’

The decreasing cost of sequencing is leading to a growing repertoire of personal genomes. However, we are lagging behind in understanding thefunctional consequences of the millions of variants obtained from sequencing. For cancer genomes, an understanding of the functional impact of mutations can help identication of drivers that lead to tumorigenesis. A large proportion of genomic variants are noncoding and their interpretation is especially challenging. In my talk, I will present integrative computational models to understand the global system-wide eects of mutations. These models combine population-scale sequencing data (from 1000 Genomes consortium), noncoding functional annotations (from ENCODE consortium) and gene interactions from biological networks (including protein-protein, regulatory and metabolic interactions). I will discuss how contrasting patterns of natural polymorphisms and somatic variants can lead to identication of cancer driver mutations. Finally, I will discuss computational tools that I have developed to prioritize variants (both coding and noncoding) in disease studies.