score in ALSPAC and the alcohol dependence symptom counts in FT12, COGA, and IASPSAD (log+1 transformed to adjust for the zero-inflated distributions). To account for multiple testing, we performed a Bonferroni p-value correction by dividing α=.05 by the number of discovery-validation pairs of analyses (23 pairs, αadj=.0022), given that scores from multiple p value thresholds within a discovery-validation set are necessarily nested within each other and not independent tests. We calculated the variance explained by the polygenic scores by comparing the R2 change between the full model and a model in which the score was dropped and only the covariates remained (Nagelkerke’s pseudo-R2 for the generalized linear mixed models, as implemented in the R package MuMIn (Bartoń, 2016)). We conducted power analyses using the pwr package in R (Champely, 2015) in order to estimate our ability to find significant effects of the polygenic risk at levels detected in studies with similar methodology.
