A PRS for an individual is a summation of their genotypes at variants genome-wide, weighted by effect sizes on a trait of interest. Effect sizes are typically estimated from published GWAS results, and only variants exceeding a P-value threshold, PT, are included. Since even large GWAS achieve only marginal evidence for association for many causal variants, PRS are usually calculated at a set of P-value thresholds, e.g. PT=1×10−5,1×10−4,…,0.05,0.1,…,0.5

PRSice will automatically calculate the PRS for different p-value thresholds and perform a regression to test the level of association of the PRS with the target phenotype. This allow users to identify the PRS that "best" predicts the phenotype and can be used for downstream analysis.


The p-value thresholds are inclusive. That is, For a p-value threshold of 0.5, all SNPs with p-value of 0.5 will also be included in this threshold.


  • --bar-levels

    Level of barchart to be plotted. When --fastscore is set, PRSice will only calculate the PRS for threshold within the bar level. Levels should be comma separated without space

  • --fastscore

    Only calculate threshold stated in --bar-levels

  • --no-full

    By default, PRSice will include the full model, i.e. p-value threshold = 1. Setting this flag will disable that behaviour

  • --interval | -i

    The step size of the threshold. Default: 0.00005

  • --lower | -l

    The starting p-value threshold. Default: 0.0001

  • --model

    Genetic model use for regression. The genetic encoding is based on the base data where the encoding represent number of the effective allele Available models include:

    • add - Additive model, code as 0/1/2 (default)
    • dom - Dominant model, code as 0/1/1
    • rec - Recessive model, code as 0/0/1
    • het - Heterozygous only model, code as 0/1/0
  • --missing

    Method to handle missing genotypes. By default, final scores are averages of valid per-allele scores with missing genotypes contribute an amount proportional to imputed allele frequency. To throw out missing observations instead (decreasing the denominator in the final average when this happens), use the no_mean_imputation modifier. Alternatively, you can use the center modifier to shift all scores to mean zero.

  • --no-regress

    Do not perform the regression analysis and simply output all PRS.

  • --score

    Method to calculate the polygenic score. Available methods include:

    • avg - Take the average effect size (default)
    • std - Standardize the effect size
    • sum - Direct summation of the effect size
  • --upper | -u

    The final p-value threshold. Default: 0.5