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Chunk #116 — Methods — Comparison with SMR

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Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics.
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On the other extreme when the GWAS association is much stronger than the eQTLs, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Z_{{\mathrm{eQTL}}} \ll Z_{{\mathrm{GWAS}}}$$\end{document}ZeQTL≪ZGWAS,16\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{\mathrm{SMR}} = \frac{{Z_{{\mathrm{eQTL}}}^2}}{{1 + \frac{{Z_{{\mathrm{eQTL}}}^2}}{{Z_{{\mathrm{GWAS}}}^2}}}} \approx Z_{{\mathrm{eQTL}}}^2\left( {1 - \frac{{Z_{{\mathrm{eQTL}}}^2}}{{Z_{{\mathrm{GWAS}}}^2}}} \right)$$\end{document}TSMR=ZeQTL21+ZeQTL2ZGWAS2≈ZeQTL21-ZeQTL2ZGWAS2