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Table 4 Functional signatures improve inference for association status in a GWAS of ovarian cancer

From: Functional annotation signatures of disease susceptibility loci improve SNP association analysis

Variant Locus MAF LOF log(BFA) RankA RankA+F
rs2072590 2q31 0.34 1.46 8.63 65 59
rs2665390 3q25 0.09 0.77 8.08 77 73
rs10069690 5p15 0.23 0.91 -1.38 1,549,122 651,710
rs11782652 8q21 0.08 0.22 2.98 5,272 6,843
rs7814937 8q24 0.12 1.54 14.61 21 16
rs3814113 9p22 0.30 -0.09 14.01 38 38
rs7084454 10p12 0.31 1.44 1.19 45,616 12,221
rs757210 17q12 0.37 1.74 2.31 11,630 2,411
rs2077606 17q21 0.18 0.70 -0.25 339,456 200,494
rs9303542 17q21 0.27 0.05 3.70 2,276 3,532
rs8170 19p13 0.19 0.82 2.72 7,133 4,179
Mean True + 0.23 0.87 5.15 178,246 80,143
Median True + 0.23 0.82 2.98 5,272 3,532
Mean True − 0.35 0.11 0.37 438,664 517,810
Median True − 0.36 0.06 0.14 181,116 244,393
  1. Ranks of known associated variants (labeled ‘true +’) tend to improve (i.e. are closer to one) when association and functional data are incorporated in the analysis (RankA+F) relative to when only the association data are used (RankA) and, hence, are more likely to be studied further. Conversely, ranks of (very likely) unassociated variants (labeled ‘true −’) tend to fall with inclusion of the functional data. The functional data for a given variant is summarized by its ‘functional signature’, defined as the prior log–odds of its association given the functional data (LOF). Aggregate (mean and median) values are provided for the true + set and the true − set. Ranks are out of approximately 2.5M variants.