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. 2020 Oct 21;48(20):11304–11321. doi: 10.1093/nar/gkaa877

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© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 6. — FAM167A-BLK ΔMGW prioritization by Frequentist and Bayesian methods in European and African Ancestries. (A) Genotyped SNPs that passed quality control and were within 250kb of the top single-SNP association analysis in EA and AA data. A 60 kb region capturing the primary peak of association is highlighted. In both the EA and AA data a cluster of SNPs in high LD yielded the top association signals. (B) Using SKAT as a ΔMGW-weighted frequentist approach, rs2061831 was sharply prioritized over SNPs in the previously identified LD blocks. While the single-SNP logistic regression analyses in (A) identified a different top SNP in the EA (rs13277113) and AA (rs2736340) data, rs2061831 was consistently prioritized as the top SNP in both the EA and AA analyses. ΔMGW-weighting did not yield spurious associations for with SNPs outside the broad 60 kb peak of association highlighted in yellow. (C) SNPs within the 60 kb association peak were analyzed by a Bayesian approach. The ΔMGW-weighted posterior probabilities are plotted. While the majority of SNPs yielded infinitesimal posterior probabilities, those comprising the 95% derived credible sets are labeled. Akin to the ΔMGW-weighted SKAT analyses, rs2061831 was again prioritized in both the EA and the AA data, with the largest posterior probability. (D) The ΔMGW is plotted for each SNP in the 60 kb region. The ΔMGW for a SNP is sequence-specific thus yielding the same values for SNPs in both the EA and AA data. Differences between the two plots result from differences in genotyped SNP lists (i.e. SNPs that are monomorphic in one population would not be plotted). SNPs identified by the derived ΔMGW-weighted credible set are plotted in yellow. While rs2061831 had a large ΔMGW, other SNPs in the region had larger magnitudes of ΔMGW but did not show evidence of SLE-association. This illustrates the importance of a two-parameter hypothesis which considers a combination of association signal and ΔMGW magnitude. Prioritized SNPs fall upstream of both FAM167A and BLK.