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A guide to performing Polygenic Risk Score analyses

View ORCID ProfileShing Wan Choi, View ORCID ProfileTimothy Shin Heng Mak, View ORCID ProfilePaul F. O’Reilly
doi: https://doi.org/10.1101/416545
Shing Wan Choi
MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
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Timothy Shin Heng Mak
Centre of Genomic Sciences, University of Hong Kong, Hong Kong, China
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Paul F. O’Reilly
MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
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Abstract

The application of polygenic risk scores (PRS) has become routine across genetic research. Among a range of applications, PRS are exploited to assess shared aetiology between phenotypes, to evaluate the predictive power of genetic data for use in clinical settings, and as part of experimental studies in which, for example, experiments are performed on individuals, or their biological samples (eg. tissues, cells), at the tails of the PRS distribution and contrasted. As GWAS sample sizes increase and PRS become more powerful, they are set to play a key role in personalised medicine. However, despite the growing application and importance of PRS, there are limited guidelines for performing PRS analyses, which can lead to inconsistency between studies and misinterpretation of results. Here we provide detailed guidelines for performing polygenic risk score analyses relevant to different methods for their calculation, outlining standard quality control steps and offering recommendations for best-practice. We also discuss different methods for the calculation of PRS, common misconceptions regarding the interpretation of results and future challenges.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted September 14, 2018.
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A guide to performing Polygenic Risk Score analyses
Shing Wan Choi, Timothy Shin Heng Mak, Paul F. O’Reilly
bioRxiv 416545; doi: https://doi.org/10.1101/416545
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A guide to performing Polygenic Risk Score analyses
Shing Wan Choi, Timothy Shin Heng Mak, Paul F. O’Reilly
bioRxiv 416545; doi: https://doi.org/10.1101/416545

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