The aim of this tutorial is to provide a simple introduction to PRS analyses to those new to PRS, while equipping existing users with a better understanding of the processes and implementation "underneath the hood" of popular PRS software. The tutorial is separated into four main sections and reflects the structure of our guide paper: the first two sections on QC corres… This tutorial provides a step-by-step guide to performing basic polygenic risk score (PRS) analyses and accompanies our PRS Guide paper. The score is typically calculated as a score for a disease, but it can be used for any trait that is affected by many different SNPs. 60 We define polygenic risk scores, or polygenic scores, as a single value estimate of an 61 individual’s propensity to a phenotype, calculated as a sum of their genome-wide genotypes 62 weighted by corresponding genotype effect sizes – potentially scaled or shrunk – … A polygenic risk score (PRS) is a score that gives you a genetic risk for something, as calculated using many SNPs at the same time. For example, consider two people with high polygenic risk scores for having coronary heart disease. A polygenic risk score tells you how a person’s risk compares to others with a different genetic constitution. However, polygenic scores do not provide a baseline or timeframe for the progression of a disease. The default formula for PRS calculation in PLINK is: $PRS_j =\frac{ \sum_i^NS_i*G_{ij}}{P*M_j}$ where the effect size of SNP $$i$$ is $$S_i$$ ; the number of effect alleles observed in sample $$j$$ is $$G_{ij}$$ ; the ploidy of the sample is $$P$$ (is generally 2 for humans); the total number of SNPs included in the PRS is $$N$$ ; and the number of non-missing SNPs observed in sample $$j$$ is $$M_j$$ .