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Chunk #10 — Results — Simulation results: power and lack of bias

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Partitioning heritability by functional annotation using genome-wide association summary statistics.
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In our first set of simulations, we assessed the power and bias of the method at a variety of settings of SNP-heritability (hg2), sample size (N), and proportion of causal SNPs (pcausal) (Online Methods). These simulations demonstrated well-calibrated type 1 error at all settings of hg2, N, and pcausal tested (Figure 1). At a fixed pcausal, power depends on N and hg2 only through N·hg2 (Supplementary Figure 1), and increases as N·hg2 increases and as pcausal increases (Figure 1a). We also looked at the z-score for total SNP-heritability in our analysis, which increases as N·hg2 and pcausal increase (Figure 1b). We found that the relationship of heritability z-score to power was the same for both values of pcausal (Figure 1c), indicating that the heritability z-score is a good indicator of power at a variety of sample sizes, heritabilities, and values of pcausal. For this paper, we chose to analyze only traits with a heritability z-score above 7, which corresponds to N·hg2 of roughly 4,500 for very polygenic traits and 12,500 for less polygenic traits.