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(26 Apr 2013,
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---+++ Department of Biostatistics Seminar/Workshop Series ---+ <a name="Identifying_Genetic_Variants"></a> Identifying Genetic Variants for Complex Traits via Sequencing: Methods and Applications ---++ <a name="Bingshan_Li_PhD"></a> Bingshan Li, !PhD ---+++ <a name="Department_of_Biostatistics"></a> Department of Biostatistics, University of Michigan ---+++ <a name="Friday_December_10_11_00am_12_00pm"></a> Friday, December 10, 11:00am-12:00pm, MCN C2209 In the past years Genome-Wise Association Studies (GWAS) have identified hundreds of common variants associated with human complex traits. However these variants collectively explain only a small proportion of genetic variance. In finding the missing heritability, sequencing is being carried out to unravel the full spectrum of genetic variation with a particular goal of identifying rare variants for complex traits. Nevertheless it is challenging to detect associated rare variants due to low frequencies and allelic heterogeneity, which is further exacerbated by sequencing errors. In the first part I will describe these challenges and propose new statistical frameworks for localizing susceptibility loci. Next I will show what we can learn about the genetic architecture of complex traits using LDL as an example, where we sequenced 9 associated loci identified in prior !SardiNIA GWAS. A crucial step for successful gene mapping through sequencing is to accurately call genotypes from sequencing data and in the final part I will describe a likelihood-based framework for efficient and accurate genotype calling in families for next generation sequencing. Its performance will be shown for both simulation data and our !SardiNIA whole genome sequencing of related individuals. * [[%ATTACHURL%/BingshanLiCV.pdf][BingshanLiCV.pdf]]: Bingshan Li CV
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Topic revision: r3 - 26 Apr 2013,
JohnBock
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