Large genetic studies often contain populations where almost all individuals are admixed. Population genetic analyses of such scenarios are difficult but one approach is to mask part of the genome so only a single ancestry remains. However, there are several challenges with this approach. Current methods for inference of local ancestry need predefined reference panels and do not scale well for large sample sizes. Subsequent analyses, like PCA, have issues dealing with missing data when there are no overlapping sites with information, a consequence of splitting an admixed individual into masked versions of its ancestries. Here, we present a framework for analyzing such data.
Kristian Ebbesen Hanghøj from the University of Copenhagen, Denmark
Profile page at University of Copenhagen.
Please note that Kristian is visiting us here at IBV/CEES and this seminar will take place in person in the Terrarium, 3315. There will be no hybrid solutions this year for the seminar series, so do please add the event to your agenda.