February 8 2012

10:00 LSB 2320

This seminar is sponsored by Computational BioSciences Initiative & the Dept of EEB

Vikas Bansal
Scripps Genomic Medicine, Scripps Translational Science Institute

Understanding human genetic variation using high-throughput sequencing: rare variants, haplotypes and human disease


Recent advances in sequencing technologies have made it possible to catalogue rare DNA sequence variants in human populations, characterize somatic mutations in cancer genomes and identify the genes involved in Mendelian disorders. Next-generation sequencing technologies also hold great promise for assessing the contribution of rare variants to risk for complex diseases. However, transforming the large amounts of raw data generated by next-generation instruments into useful biological information poses significant computational and statistical challenges. In the context of sequencing-based association studies for complex diseases, two major challenges are the detection and genotyping of variants from sequence reads and association analysis for rare variants. In this talk, I will describe a probabilistic method for the accurate detection and genotyping of SNVs and short indels from population-scale sequence data. I will also describe statistical methods for rare variant association mapping. To enable the cost-efficient sequencing of specific genomic regions in thousands of individuals, we have developed an approach that combines DNA pooling, in-solution target-enrichment technology and a novel statistical framework for variant detection and association analysis from pooled sequence data. I will describe results from the application of these methods to association studies for several complex diseases.
Although humans are diploid, virtually all sequencing studies of human genetic variation ignore phase or haplotype information. I will talk about the importance of phase information in human genomics and describe algorithms for assembling haplotypes for an individual directly from whole-genome sequence data. Finally, I will briefly describe an approach for understanding the functional consequences of genetic variation in an individual diploid genome by integrating whole-genome haplotype information and RNA-seq data.

Hosted by Professor Bob Wayne















































































































































































































































































































































































































































































































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