Applied population genetics

I have been involved in quite a few applied population genetics projects. A recent example is a study where we looked for signatures of genetic adaptation to life in the Arctic in Greenlandic Inuit. In this study we identified a genomic region on chromosome 11, which, based on the so-called PBS statistic, showed evidence for having been under positive selection.


Subsequently, using association testing we found evidence supporting that our finding was a case of adaptation to the traditional high-fat diet that the Arctic environment has historically imposed on the Greenlandic Inuit. For details see Fumagalli*, Moltke* et al. (2015).

I have also been involved in numerous studies focusing on how the world was peopled. For examples of these and of other selection studies I have been involved in see the following papers:

Method development for population genetics studies

Since I started my PhD, I have had an interest in developing statistic inference methods for studies in population genetics. More specifically I am interested in inference of relatedness and selection and in doing so when data is either limited or from admixed individuals. For examples see

Applied medical genetics

I am currently involved in several different mapping studies in the Greenlandic population. One example is a study of type 2 diabetes where we identified a stop-gain mutation in the gene TBC1D4 that significantly increases homozygous carrier risk of getting type 2 diabetes (OR 10.3):


For more info see Moltke et al. 2014, Nature. And for other examples see:

Method development for medical genetics studies

I am also involved in several projects about developing methods for mapping diseases and other traits. One example is a study where we developed an MCMC based method for mapping of disease cause by a low number of founder mutations based on IBD inference. In a proof of concept we showed it could be used for mapping using as few as 5 breast cancer cases:


For more info about that study see Moltke et al. 2011, Genome Research and for other examples of studies I have been involved in see: