TABLE 1.

Comparison between CV and RV association analysis.

Considerations	CV association analysis	RV association analysis
Assays	Typically captured using inexpensive genotyping microarrays	Often requires NGS, especially for detecting extremely rare/novel variants
Number of variants tested	Often single variant based (e.g., GWAS)	Often multiple variants based due to low power of single-variant methods
Population structure	Confounding can be adequately controlled using PCA or mixed models	Rare variants are likely more recent and reflect finer subpopulations. May need either more PCs or specifically designed methods
Null distributions of test statistics	Ordinary asymptotic distributions work well	Null distributions are often complex mixtures and more sophisticated methods may be necessary
Use of annotations	Statistical test for each variant is often performed without relying on annotations	Due to the large number of rare variants in a region, annotations are often used to filter rare variants
Interpretation	Due to potential LD, single-variant associations may be tag-SNPs	May be unclear which RVs are “driving” a significant RV association result using aggregative testing, especially those considering both directions