Room 200 HECC
Chad Huff, Assistant Professor (at MD Anderson Cancer Center)
Abstract: Advances in high-throughput sequencing technologies are transforming the landscape of biomedical research. As the generation of genomic data becomes commoditized, research efforts are increasingly being shifted to data analysis and interpretation. Traditional genetic analysis approaches designed for sparse marker data are often suboptimal in large sequencing studies due to problems related to low power and computational scalability. In this talk, I will present an overview of the bioinformatics tools my group has developed to analyze high-throughput sequencing data. Topics will include relationship estimation, pedigree reconstruction, functional variant prediction, and analysis of rare variants in both familial and case-control studies. I will describe Estimation of Recent Shared Ancestry (ERSA), a method for detecting genetic relationships that can identify cryptic relatives as distant as 4th cousins and can aid in the partial reconstruction of extended pedigrees. I will also present the Variant Annotation, Analysis, and Search Tool (VAAST), a probabilistic disease-gene finder that combines amino acid substitution and allele frequency information to improve the power of case-control sequencing studies. I will conclude with a discussion of pedigree-VAAST (pVAAST), a new method for conducting familial disease-gene sequencing studies that combines linkage analysis, case-control association, and variant prioritization in a unified statistical framework.
BIO: Research in my lab is concentrated on understanding human evolution and the genetic basis of human disease through statistical, computational, and population genomics. My work spans a number of human genetics subdisciplines, including disease-gene identification, relationship estimation, pedigree reconstruction, mutation rate estimation, detection of recent positive selection, and reconstruction of demographic history. My group is currently focused on developing new methods to analyze genomic data and applying these methods to discover novel insights about the genetic basis of human disease, with particular emphasis on identifying and characterizing genes that increase the risk of developing common cancers.
Host: Dr. Khatri