University of Michigan, Center for Statistical Genetics
Presents
CSG Seminar Speaker
Yun Song
University of California, Berkeley
Speaking On:
Identifiability of demographic models and distortion of genealogical properties for very large samples.
Study sample sizes in human genetics are growing rapidly, and in due course it will become routine to analyze samples with hundreds of thousands, if not millions, of individuals. In addition to posing computational challenges, such large sample sizes call for carefully reexamining the theoretical foundation underlying commonly used analytical tools. The coalescent is a central model in modern population genetics for studying the ancestry of a sample of individuals. It arises as a limit of a large class of random mating models, and it is an accurate approximation to the original model provided that the population size is sufficiently larger than the sample size. In this talk, I will present new theoretical results on the identifiability of demographic models under the coalescent. I will also characterize quantitatively the extent to which the coalescent continues to provide a good approximation in the case where the sample size increases to the point that the coalescent assumption may be violated.
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Monday, April 7, 2014
12:00 P.M.
1655, SPH I
Assistant to Dr. Michael Boehnke
Center for Statistical Genetics
University of Michigan
Department of Biostatistics
1415 Washington Heights, M4242
Ann Arbor, MI 48109
