Single Nucleotide Polymorphisms (SNPs) are nucleotide positions in the genome that may vary among individuals from the same species or
population. Patterns of variation among linked and unlinked SNPs may contain a great deal of information regarding the evolutionary
history of populations and species including demographic, genomic,and selective processes.
The purpose of this talk is to discuss recent advances in statistical population genetics for the analysis of SNP data. Four specific
examples will be discussed: (1) identifying evidence of a selective sweep for non-stationary population genetic models, (2) estimating
the local recombination rate (including variation in rate) as well as placing bounds on our uncertainty, (3) detecting evidence of
population substructure for species that undergo self-fertilization,and (4) joint estimation of population size change and natural selection. This talk will cover joint work with Scott Williamson, Rasmus Nielsen, Andrew Clark, Jeff Jensen, Lan Zhu, Hong Gao, and Ryan Hernandez.
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