Eran Halperin, International Computer Science Institute

Title: Estimating Local Ancestry in Admixed Populations

Large-scale genotyping of SNPs has shown a great promise in identifying markers that could be linked to diseases. 
One of the major obstacles involved in performing these studies is that the underlying population sub-structure 
could produce spurious associations. Population sub-structure can be caused by the presence of two distinct 
sub-populations or a single pool of admixed individuals. In this talk, I will focus on the latter which is significantly 
harder to detect in practice. New advances in this research direction are expected to play a key role in identifying loci 
which are different among different populations and are still associated with a disease. Furthermore, the detection of 
an individual ancestry has important medical implications. I will describe two methods that we have 
recently developed to detect admixture, or the locus-specific ancestry in an admixed population. We have run extensive 
experiments to characterize the important parameters that have to be optimized when 
considering this problem - I will describe the results of these experiments in context with existing tools such as SABER and STRUCTURE.