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

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 inef...

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Vydáno v:Nucleic acids research Ročník 52; číslo W1; s. W70 - W77
Hlavní autoři: Forer, Lukas, Taliun, Daniel, LeFaive, Jonathon, Smith, Albert V, Boughton, Andrew P, Coassin, Stefan, Lamina, Claudia, Kronenberg, Florian, Fuchsberger, Christian, Schönherr, Sebastian
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Oxford University Press 05.07.2024
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ISSN:0305-1048, 1362-4962, 1362-4962
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Shrnutí: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.
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ISSN:0305-1048
1362-4962
1362-4962
DOI:10.1093/nar/gkae331