Extended Data Fig. 8: False positive rate (FPR) for ACAT-V, fastGWA-BB, and REGENIE-Burden under different simulation scenarios.
From: A generalized linear mixed model association tool for biobank-scale data
Three gene-based test methods are compared in this analysis, that is, ACAT-V (implemented in GCTA), fastGWA-BB, and REGENIE-Burden. The y-axis represents the FPR computed from the null genes (that is, all the 1,224 genes on chromosome 1 under the null simulation scenarios), and “Prev” on the x-axis represents different levels of simulated prevalence of the binary trait. The prevalence is defined as \(n_{case}/(n_{case} + n_{control})\)). FPR is evaluated at five different alpha levels (α=0.05, 0.01, 0.005, 0.001, and 5×10−4), as shown in panels from a) to e), repectively. The dashed lines indicate the expected FPRs (that is, the alpha levels). Each boxplot represents the distribution of FPR 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 dot. 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.
