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. 2015 May 1;31(9):1466-8.
doi: 10.1093/bioinformatics/btu848. Epub 2014 Dec 29.

PRSice: Polygenic Risk Score software

Jack Euesden  1 , Cathryn M Lewis  1 , Paul F O'Reilly  1
Affiliations
Free PMC article

PRSice: Polygenic Risk Score software

Jack Euesden et al. Bioinformatics. .
Free PMC article

Abstract

Summary: A polygenic risk score (PRS) is a sum of trait-associated alleles across many genetic loci, typically weighted by effect sizes estimated from a genome-wide association study. The application of PRS has grown in recent years as their utility for detecting shared genetic aetiology among traits has become appreciated; PRS can also be used to establish the presence of a genetic signal in underpowered studies, to infer the genetic architecture of a trait, for screening in clinical trials, and can act as a biomarker for a phenotype. Here we present the first dedicated PRS software, PRSice ('precise'), for calculating, applying, evaluating and plotting the results of PRS. PRSice can calculate PRS at a large number of thresholds ("high resolution") to provide the best-fit PRS, as well as provide results calculated at broad P-value thresholds, can thin Single Nucleotide Polymorphisms (SNPs) according to linkage disequilibrium and P-value or use all SNPs, handles genotyped and imputed data, can calculate and incorporate ancestry-informative variables, and can apply PRS across multiple traits in a single run. We exemplify the use of PRSice via application to data on schizophrenia, major depressive disorder and smoking, illustrate the importance of identifying the best-fit PRS and estimate a P-value significance threshold for high-resolution PRS studies.

Availability and implementation: PRSice is written in R, including wrappers for bash data management scripts and PLINK-1.9 to minimize computational time. PRSice runs as a command-line program with a variety of user-options, and is freely available for download from http://PRSice.info

Contact: jack.euesden@kcl.ac.uk or paul.oreilly@kcl.ac.uk

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

Fig. 1.
Fig. 1.
Bar plot from PRSice showing results at broad P-value thresholds for Schizophrenia PRS predicting MDD status. A bar for the best-fit PRS from the high-resolution run is also included
Fig. 2.
Fig. 2.
High-resolution PRSice plot for SCZ predicting MDD status. The thick line connects points at the broad P-value thresholds of Fig.1
See this image and copyright information in PMC

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