Extended Data Fig. 7: Mean χ2 value of the causal variants for fastGWA-GLMM and fastGWA-GLMM-Ped under different simulation scenarios.
From: A generalized linear mixed model association tool for biobank-scale data
FastGWA-GLMM-Ped: fastGWA-GLMM using the pedigree relatedness matrix. fastGWA-GLMM: fastGWA-GLMM using the sparse GRM. The y-axis represents the mean χ2 value of the causal variants (10,000 common and 1,000 rare causal variants on the odd chromosomes), and the x-axis represents different levels of prevalence of the simulated binary phenotypes (prevalence \(= n_{case}/(n_{case} + n_{control})\)). Apart from being evaluated for the 11,000 variants altogether in panel a), the mean χ2 value is also evaluated for common (MAF ≥ 0.01) and rare (MAF < 0.01) causal variants separately, as shown in panels b) and c) respectively. Each boxplot represents the distribution of mean χ2 across 100 simulation replicates. The line inside each box indicates the median value, notches indicate the 95% confidence interval, central box indicates the interquartile range (IQR), whiskers indicate data up to 1.5 times the IQR, and outliers are shown as separate dots. In all the analyses, we used a one-sided \(\chi _{\mathrm{d.f.} = 1}^2\) statistic to test against the null hypothesis of no association.
