PRSice is a software package for calculating, applying, evaluating and plotting polygenic risk scores (PRS). PRS are sums of trait-associated alleles across many genetic loci, weighted by effect sizes from genome-wide association studies (GWAS). PRSice can calculate PRS at multiple P-value thresholds to find the best-fit PRS, thin SNPs based on linkage disequilibrium or P-value, and handle both genotyped and imputed data. It can also incorporate ancestry-informative variables and apply PRS across multiple traits in a single run. PRSice is written in R and includes wrappers for bash scripts and PLINK-1.9 to minimize computational time. It is a command-line program with various user options and is freely available at http://PRSice.info. PRSice was used to test for shared genetic aetiology between traits, such as schizophrenia (SCZ) and major depressive disorder (MDD). Applying PRSice to the RADIANT-UK MDD case-control dataset, it was found that SCZ PRS predicted MDD status, with the best-fit PRS at P_T=0.05 explaining 1.5% of the variation in MDD. Using high-resolution PRS, the best-fit PRS at P_T=0.0265 explained 2.1% of the variation in MDD, based on 5252 fewer SNPs. PRSice was also applied to two tobacco-related phenotypes, revealing shared genetic aetiology between the dichotomous trait 'ever smoked' and MDD, but not between smoking consumption and MDD. A permutation study estimated an adjusted significance threshold of P=0.004 for the best-fit PRS. The authors suggest a more conservative threshold of P=0.001 for association testing in PRS studies. PRSice has the potential to expand the application of PRS in genetics, providing insights into the genetic architecture of traits, assessing genetic overlap across populations, and serving as biomarkers or instrumental variables. The software could also be extended to test the effects of copy number variants, epigenetic markers, and more. PRSice is expected to simplify PRS studies, expand their application, and aid the implementation of best practices in PRS research.PRSice is a software package for calculating, applying, evaluating and plotting polygenic risk scores (PRS). PRS are sums of trait-associated alleles across many genetic loci, weighted by effect sizes from genome-wide association studies (GWAS). PRSice can calculate PRS at multiple P-value thresholds to find the best-fit PRS, thin SNPs based on linkage disequilibrium or P-value, and handle both genotyped and imputed data. It can also incorporate ancestry-informative variables and apply PRS across multiple traits in a single run. PRSice is written in R and includes wrappers for bash scripts and PLINK-1.9 to minimize computational time. It is a command-line program with various user options and is freely available at http://PRSice.info. PRSice was used to test for shared genetic aetiology between traits, such as schizophrenia (SCZ) and major depressive disorder (MDD). Applying PRSice to the RADIANT-UK MDD case-control dataset, it was found that SCZ PRS predicted MDD status, with the best-fit PRS at P_T=0.05 explaining 1.5% of the variation in MDD. Using high-resolution PRS, the best-fit PRS at P_T=0.0265 explained 2.1% of the variation in MDD, based on 5252 fewer SNPs. PRSice was also applied to two tobacco-related phenotypes, revealing shared genetic aetiology between the dichotomous trait 'ever smoked' and MDD, but not between smoking consumption and MDD. A permutation study estimated an adjusted significance threshold of P=0.004 for the best-fit PRS. The authors suggest a more conservative threshold of P=0.001 for association testing in PRS studies. PRSice has the potential to expand the application of PRS in genetics, providing insights into the genetic architecture of traits, assessing genetic overlap across populations, and serving as biomarkers or instrumental variables. The software could also be extended to test the effects of copy number variants, epigenetic markers, and more. PRSice is expected to simplify PRS studies, expand their application, and aid the implementation of best practices in PRS research.