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Center for Nonlinear Studies |
In the fist part of this talk I will present a full likelihood-based inference method for population genetic data when the genealogies of DNA sequences fit into the general coalescent tree framework and mutations in DNA sequences are modeled in the infinite-sites model. The general coalescent tree framework is a family of genealogical models, including genealogical models derived for various demographic scenarios. First I will describe an exact sampling scheme for determining the topologies of the conditional ancestral trees. This scheme, however, has some computational limitations and to overcome these limitations a second scheme based on an importance sampling will be provided. These schemes are combined with Monte Carlo integrations to estimate the likelihood of full polymorphism data, the ages of mutations in the sample, and the time of the most recent common ancestor. I will give some applications of this method. In the second part of my talk I will briefly present my current project for developing coalescent based inference methods for genetic data from HIV patients.
Host: Peter Loxley, loxley@lanl.gov