in dosage data from Yale-Penn 1-3. The dosage genotypes for each cohort were transformed into hard call genotypes with PLINK1.9 (5). Using hard-call genotypes to analyze imputed GWAS genotypes has been reported previously (9). In our study, the dosage genotypes for each cohort were transformed into hard call genotypes with PLINK1.9, the rationale for which was to keep only high-quality dosage data by filtering with stricter QC parameters of genotype probability (GP >=0.9) using Plink1.9. The high-quality hard-call genotyping data are easier to QC with Plink1.9 than dosage data, and the genotype data can be directly used in association tests with GEMMA (Genome-wide Efficient Mixed Model Association) (10) (improving the efficiency of computation), which incorporates and account for the relatedness among our family samples and model the relatedness to increase statistical power. Only genotypes with genotype imputation probability (GP) ≥0.9, an individual genotyping missing rate <5%, MAF >1% and missing call frequency <5% were kept for the association analysis. Following these QC efforts, there were ∼13 M, ∼9.8 M, and ∼5.9 M variants left for Yale-Penn 1-3, respectively.
