Introduction¶
A PRS for an individual is a summation of their genotypes at variants genomewide, weighted by effect sizes on a trait of interest. Effect sizes are typically estimated from published GWAS results, and only variants exceeding a Pvalue 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 Pvalue thresholds, e.g. PT=1×10^{−5},1×10^{−4},…,0.05,0.1,…,0.5
PRSice will automatically calculate the PRS for different pvalue 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.
Note
The pvalue thresholds are inclusive. That is, For a pvalue threshold of 0.5, all SNPs with pvalue of 0.5 will also be included in this threshold.
Command¶

barlevels
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
barlevels

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

interval
i
The step size of the threshold. Default: 0.00005

lower
l
The starting pvalue 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 0/1/1rec
 Recessive model, code as 0/0/1het
 Heterozygous only model, code as 0/1/0

missing
Method to handle missing genotypes. By default, final scores are averages of valid perallele 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 thecenter
modifier to shift all scores to mean zero. 
noregress
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 sizesum
 Direct summation of the effect size

upper
u
The final pvalue threshold. Default: 0.5