The first phase of quality control analyses, including assessment of Hardy-Weinberg equilibrium, differential missingness, platform effects, population stratification, and genotyping call rate, was conducted as a part of the recently published GWAS of OCD and TS [30], [31]. The variance components models in the REML analysis utilized all unpruned genotype data simultaneously. Because all genotypes are fitted together in a given variance component, these components are particularly susceptible to minor technical and experimental artifacts that might only modestly affect each genotype (i.e., in a SNP-by-SNP test of association) but could have a substantial cumulative global effect on the results from a mixed linear model. We thus undertook additional, more stringent quality control measures to minimize any possible persistent population stratification and experimental bias. Prior to case-control comparisons, we first focused solely on the control dataset to develop our QC pipeline. We split the controls by data source (iControl vs. SAGE controls) and performed the following QC steps using PLINK. We implemented stringent thresholds and removed additional SNPs showing low levels of differential missingness between cases and controls (p<0.05), modest deviation
