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Ming Li, University of Arkansas for Medical Science
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| Title: Random Field Modelling of Genetic Association for Sequencing Data |
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Abstract: With the advance of high-throughput sequencing technologies, it has become feasible to investigate the influence of the entire spectrum of sequencing variations on complex human diseases. Although association studies utilizing the new sequencing technologies hold great promise to unravel novel genetic variants, especially rare genetic variants that contribute to human diseases, the statistical analysis of high-dimensional sequencing data remains a challenge. Advanced analytical methods are in great need to facilitate high-dimensional sequencing data analyses. In this talk, we will introduce a generalized genetic random filed (GGRF) method for association analyses of sequencing data in case-control studies. We will then further extend GGRF method to a family-based GGRF (FB-GGRF) method for family-based association studies. Both GGRF and FB-GGRF methods are compared with other existing methods through simulation studies and real data applications for investigating the genetic etiology of complex diseases/traits.
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