Fig 1.
FDR at a cutoff of 1.95 (p-value 0.05 for a normally distributed test) is the ratio of the area of the light blue region divided by the area of (beige plus light blue). LFDR compares the height of the dark blue line to the height of the brown line.
Table 1.
Number of SNPs by minor allele frequency bins, as well as the number and percentage of significant SNPs, using several definitions of statistical significance.
Table 2.
Observed heritability (h2 obs) and its standard error (SE), expected heritability (h2 exp) and the adjusted P-value from LD-score regression for enrichment in CAD.
Also, the distances between p-value distributions (D-statistics) from Kolmogorov-Smirnov tests are shown, comparing different MAF groups: (a) [0.005–0.01) vs. [0.01–0.05); (b) [0.005–0.001) vs. (≥0.05); (c) [0.01–0.05) vs. (≥0.05).
Fig 2.
Changes in LFDR estimates between unadjusted LFDR and LFDR estimated with the ME method, when each of nine functional annotations are used to define a high risk subset of SNPs.
Within each panel, the three distributions are divided by p-value ranges: unadjusted p<0.05; unadjusted p<0.01; unadjusted p<0.001.
Fig 3.
LFDR estimates with the ME method, as a function of the –log(10) of the raw p-values, for all nine SNP annotation categories considered.
Fig 4.
Histogram of LFDR differences for three MAF categories using the Enhancer Hoffman.extended.500 annotation.
Differences are on an 0.25 power scale. (Left) MAF between 0.005 and 0.01. (Middle) MAF between 0.01 and 0.05. (Right) MAF greater than 0.05.
Fig 5.
Scatter plot of the LFDR-ME estimates by minor allele frequency and the decrease in LFDR estimates using the ME method, when using the H3K9ac annotation.