Introduction to Genomic Research for Clinicians — PRS QC Explained
A clinician-friendly explanation of quality control for polygenic risk scores (PRS).
What is a PRS?
A Polygenic Risk Score (PRS) is a numerical estimate of an individual’s disease risk derived by combining the effects of many genetic variants (SNPs).
Why does QC matter?
Computing a PRS requires many pre-processing steps. Without appropriate quality control (QC), reliable results cannot be obtained.
Key QC steps
1. Genotyping QC
- Filtering by missingness rate
- Filtering by minor allele frequency (MAF)
- Hardy–Weinberg equilibrium testing
2. Population stratification correction
Principal component analysis (PCA) is used to correct for the influence of population structure.
3. PRS calculation
Using base GWAS summary statistics, a PRS is computed for each individual.
Outlook for clinical applications
PRS is expected to become an important tool for realising precision medicine in the future. Applied research is advancing particularly in the areas of cardiovascular disease, cancer, and psychiatric disorders.
I hope this article helps clinicians develop a better understanding of genomic research.