Michigan Imputation Server

The Michigan Imputation Server (https://imputationserver.sph.umich.edu) is an ongoing collaboration with the University of Michigan (USA) and the EURAC research centre (Italy). It provides a free genotype imputation service for genome-wide association studies (GWAS). With >90.2 million imputed genomes, >6,800 active users and >2000 citations of the Nature Genetics paper published in 2016, it is the central backbone for GWAS worldwide.

One aim of the Michigan Imputation Server is to provide population-specific reference panels, in order to improve imputation for non-European individuals. For example, the Michigan Imputation Server supports the Genome Asia reference panel, which includes a whole-genome sequencing reference dataset from 1,739 individuals in 219 population groups and 64 countries across Asia and facilitates genetic studies of Asian populations (Nature 2019). Another example is the TOPMed-based imputation reference panel, which includes 97,256 individuals with 308,107,085 SNPs and indels (TOPMed Imputation Server). For COVID-19 related studies, we are also providing a HLA reference panel. All the services and reference panels mentioned are free of charge for academic and non-academic users worldwide.

The current focus of this research project is on the development of new methods for automation of the overall imputation process (e.g. by using an API), on the calculation of genetic risk scores (e.g. via the PGS catalogue) included within each imputation, and on the improvement and maintenance of the Michigan Imputation Server.


Michigan Imputation Server is available as a web-service or on GitHub.


Lukas Forer, PhD
Senior Scientist

+43 512 9003 70562
Sebastian Schönherr, Dr.
Senior Scientist

+43 512 9003 70579


Das S, Forer L, Schönherr S*, Sidore C, Locke AE, Kwong A, Vrieze SI, Chew EY, Levy S, McGue M, Schlessinger D, Stambolian D, Loh PR, Iacono WG, Swaroop A, Scott LJ, Cucca F, Kronenberg F, Boehnke M, Abecasis GR, Fuchsberger C: Next-generation genotype imputation service and methods. Nat. Genet. 48:1284-1287, 2016. PMID: 27571263