Imputation Server PGS: an automated approach to calculate polygenic risk scores on imputation servers

Author:

Forer Lukas1ORCID,Taliun Daniel23,LeFaive Jonathon4ORCID,Smith Albert V4,Boughton Andrew P4,Coassin Stefan1ORCID,Lamina Claudia1ORCID,Kronenberg Florian1ORCID,Fuchsberger Christian145,Schönherr Sebastian1ORCID

Affiliation:

1. Institute of Genetic Epidemiology, Medical University of Innsbruck , Innsbruck , Austria

2. Canada Excellence Research Chair in Genomic Medicine, McGill University , Montreal , Québec, Canada

3. Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University , Montréal, Québec, Canada

4. Department of Biostatistics and the Center for Statistical Genetics, University of Michigan , Ann Arbor , MI 48109 , USA

5. Institute for Biomedicine , Eurac Research, Bolzano , Italy

Abstract

Abstract Polygenic scores (PGS) enable the prediction of genetic predisposition for a wide range of traits and diseases by calculating the weighted sum of allele dosages for genetic variants associated with the trait or disease in question. Present approaches for calculating PGS from genotypes are often inefficient and labor-intensive, limiting transferability into clinical applications. Here, we present ‘Imputation Server PGS’, an extension of the Michigan Imputation Server designed to automate a standardized calculation of polygenic scores based on imputed genotypes. This extends the widely used Michigan Imputation Server with new functionality, bringing the simplicity and efficiency of modern imputation to the PGS field. The service currently supports over 4489 published polygenic scores from publicly available repositories and provides extensive quality control, including ancestry estimation to report population stratification. An interactive report empowers users to screen and compare thousands of scores in a fast and intuitive way. Imputation Server PGS provides a user-friendly web service, facilitating the application of polygenic scores to a wide range of genetic studies and is freely available at https://imputationserver.sph.umich.edu.

Funder

Medical University of Innsbruck

Publisher

Oxford University Press (OUP)

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