We estimated pairwise local rg using LAVA.22 LAVA complements MiXeR by estimating local rg across 2495 semi-independent genetic loci of approximately equal size (~1Mb), thus capable of identifying mixed effect directions despite minimal rg. LAVA differs from MiXeR because it 1) uses a distinct statistical framework based on a fixed effects model, rather than MiXeR’s random effects model, 2) identifies specific shared loci, and 3) is only a proxy measure of genome-wide genetic overlap since the number of significantly correlated loci is, in part, influenced by the statistical power of input GWAS.22 After computing local h2SNP estimates for each trait, LAVA computes the matrix of local genetic covariance for each locus using the method of moments. Sample overlap was controlled using LDSC.23 Significance testing was performed using simulation-based p-values. We used the false discovery rate (FDR) to adjust for multiple testing, reporting loci with FDR<0.05.
