Table 4.

Recommendations for Novel Variant Discovery Efforts

Recommendation	Rationale
Use genome-wide array	Tests entire genome. Can be imputed. Capable of easy meta-analysis. Straightforward ancestry correction. Helps avoid costly false-positives.
Imputation	Increases association power. Easy replication by other groups. Improves ability to finely map an association locus. Allows tests of non-SNP genetic variants.
Power	Sample sizes for GWAS of endophenotypes will require >10,000 samples to make robust discoveries because the effects of common variants on endophenotypes will be small, almost certainly less than r2=0.005 and probably less than r2=0.0005. This recommendation holds even for so-called “enriched” studies of phenotypic extremes or highly precise measurements. Using GREML to investigate genetic architecture and the covariance between the endophenotype and clinical phenotype requires smaller but still quite large samples.
Bonferroni threshold	If purpose is to identify variants for follow-up functional testing, a Bonferroni threshold of 5×10−8 will control family-wise error rate and reduce costly false positives.
Meta-analysis	The simplest way to increase statistical power is to join forces and data with like-minded people with similar data.
Replication	If outright meta-analysis of all variants is not possible, then attempt to meta-analyze top hits from your study.