Since different brain disorders have different numbers of significantly associated genes, we tried to avoid selecting genes based on a P-value threshold. In comparing H-MAGMA outputs with DEG, we used the gene-set analysis embedded in MAGMA, which utilizes the whole gene-level association statistics while controlling for covariates such as gene size and LD2. In comparing H-MAGMA outputs (common variation) with the gene lists that harbor protein disrupting variation (rare variation), we used a generalized linear model controlling for the exome length (controlling for rare variation) and the number of SNPs mapped to each gene (controlling for common variation).
