# Table 1 Estimates of α in simulations

α $${\mathrm{h}}_{\mathrm{g}}^{2}$$ Sample size Polygenicity (%) Imputation noise LD dependent effects Mean $$\hat{\mathbf{\alpha}}$$ Mean $$\hat{\mathbf{\alpha}} _{\mathrm{noLD}}$$
−0.3 0.4 5000 1 Yes Yes −0.276 ± 0.017 −0.192 ± 0.019
0.0 0.4 5000 1 Yes Yes 0.021 ± 0.020 0.120 ± 0.017
−0.6 0.4 5000 1 Yes Yes −0.573 ± 0.014 −0.471 ± 0.015
−0.3 0.2 5000 1 Yes Yes −0.260 ± 0.024 −0.148 ± 0.024
−0.3 0.4 5000 100 Yes Yes −0.308 ± 0.012 −0.195 ± 0.013
−0.3 0.4 5000 1 No Yes −0.304 ± 0.016 −0.191 ± 0.017
−0.3 0.4 5000 1 Yes No −0.373 ± 0.017 −0.284 ± 0.017
−0.3 0.4 2500 1 Yes Yes −0.269 ± 0.026 −0.157 ± 0.025
−0.3 0.2 2500 1 Yes Yes −0.266 ± 0.052 −0.160 ± 0.034
1. We simulated phenotypes using imputed UK Biobank genotypes and applied our method to infer α. In each line we show results from phenotypes that were simulated using various values of α, $$h_g^2$$, sample size, and the proportion of causal SNPs. In most simulations, imputation noise and LD dependent SNP effects were included in the simulated phenotypes. In each case we report the mean estimated α and standard error of the mean, using our estimation method either with LD correction $$\left( {\hat \alpha } \right)$$ or without LD correction $$\left( {\hat \alpha _{{\mathrm{noLD}}}} \right)$$.