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Chunk #90 — Methods — Calculation of Z-score

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Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics.
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To assess the significance of the association, we need to compute the ratio of the estimated effect size \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat \gamma _g$$\end{document}γ^g and standard error se(\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat \gamma _g$$\end{document}γ^g), or Z-score,9\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Z_g = \frac{{\hat \gamma _g}}{{{\mathrm{se}}(\hat \gamma _g)}}$$\end{document}Zg=γ^gse(γ^g)