Polygenic risk scores (PRS), which summarize the effects of genome-wide genetic markers to measure the genetic liability to a trait or a disorder, have shown promise in predicting human complex traits and diseases, and may facilitate early detection, risk stratification, and prevention of common complex diseases in healthcare settings. Here we provide two tools, PRSice-2 and PRS-CS, to calculate PRS for users own choice. PRSice-2 is the updated version of PRSice, which was used in many studies. PRS-CS is a newly developed method which utilizes a high-dimensional Bayesian regression framework to calculate the PRS. More details of these two tools can be found in the original publications.
PGC2 GWAS: Schizophrenia Working Group of the Psychiatric Genomics Consortium. 2014. Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511(7510):421-427. [PMID: 25056061]
CLOZUK GWAS: Pardiñas et al. 2018. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nature Genetics, 50(3):381-389. [PMID: 29483656]
PRSice-2: Choi et al. 2019. PRSice-2: Polygenic Risk Score Software for Biobank-Scale Data. GigaScience, 8(7):giz082. [PMID: 31307061]
PRS-CS: Ge et al. 2019. Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nature Communications, 10(1):1776. [PMID: 30992449]