| Title: | Imputation Server PGS: an automated approach to calculate polygenic risk scores on imputation servers |
| Journal: | Nucleic Acids Research |
| Published: | 6 May 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38709879/ |
| DOI: | https://doi.org/10.1093/nar/gkae331 |
| Citations: | 2 (2 in last 2 years) as of 8 Aug 2024 |
Publication 12139
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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.</p>
10 Keywords
- Alleles
- Genetic Predisposition to Disease
- Genetic Risk Score
- Genome-Wide Association Study
- Genotype
- Humans
- Internet
- Multifactorial Inheritance
- Polymorphism, Single Nucleotide
- Software
10 Authors
- Lukas Forer
- Daniel Taliun
- Jonathon LeFaive
- Albert V Smith
- Andrew P Boughton
- Stefan Coassin
- Claudia Lamina
- Florian Kronenberg
- Christian Fuchsberger
- Sebastian Schönherr
1 Application
| Application ID | Title |
|---|---|
| 62905 | Analyzing unmappable ("camouflaged") genome regions in UK Biobank exome sequencing data using the LPA gene as a model. |
Enabling scientific discoveries that improve human health