Simulated Dataset #1
In these simulated data for 2000 individuals, we assumed 99% of genomewide SNPs to be noncausal SNPs (i.e. under Null hypothesis with heritability=0) with their association pvalues Uniformly distributed and remaining 1% SNPs to be causal SNPs with their heritability between 0 and 0.01 and distribution shape as Beta(0.5, 1.5).
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Simulated Dataset #2
In these simulated data for 2000 individuals, we assumed 99% of genomewide SNPs to be noncausal SNPs (i.e. under Null hypothesis with heritability=0) with their association pvalues Uniformly distributed and remaining 1% SNPs to be causal SNPs with their heritability between 0 and 0.05 and distribution shape as Beta(0.5, 1.5).
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Simulated Dataset #3
In these simulated data for 2000 individuals, we assumed 99% of genomewide SNPs to be noncausal SNPs (i.e. under Null hypothesis with heritability=0) with their association pvalues Uniformly distributed and remaining 1% SNPs to be causal SNPs with their heritability between 0 and 0.1 and distribution shape as Beta(0.5, 1.5).
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Simulated Dataset #4
In these simulated data for 2000 individuals, we assumed 99% of genomewide SNPs to be noncausal SNPs (i.e. under Null hypothesis with Odds Ratio=1) with their association pvalues Uniformly distributed and remaining 1% SNPs to be causal SNPs with the Odds Ratio between 1.0 and 1.5 and distribution shape as Beta(0.5, 1.5).
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Simulated Dataset #5
In these simulated data for 2000 individuals, we assumed 99% of genomewide SNPs to be noncausal SNPs (i.e. under Null hypothesis with Odds Ratio=1) with their association pvalues Uniformly distributed and remaining 1% SNPs to be causal SNPs with the Odds Ratio between 1.0 and 2.0 and distribution shape as Beta(0.5, 1.5).
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Simulated Dataset #6
In these simulated data for 2000 individuals, we assumed 99% of genomewide SNPs to be noncausal SNPs (i.e. under Null hypothesis with Odds Ratio=1) with their association pvalues Uniformly distributed and remaining 1% SNPs to be causal SNPs with the Odds Ratio between 1.0 and 2.5 and distribution shape as Beta(0.5, 1.5).
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