Building Evolutionary Trees from SNPs Data: An Ancestral Mixture Models Approach

Abstract

An ancestral mixture model is proposed for clustering discrete multivariate sequences. This model has a natural relationship to the coalescent process of population genetics. The sieve parameter in the model plays an important role of time in the evolutionary tree of the sequences. In this talk, I will show how an ancestral mixture model can be used to build up a hierarchical tree from binary sequence data by sliding the sieve parameter. An example genetic single nucleotide polymorphisms (SNP) data will be used for illustration. Some properties of the ancestral mixture model, such as its nested structure and the relationship to the coalescent process of population genetics, will be presented. This is a joint work with Professor Bruce Lindsay at Penn State University.