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Chunk #8 — Results — Protocol to integrate array and WGS data

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GAWMerge expands GWAS sample size and diversity by combining array-based genotyping and whole-genome sequencing.
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WGS-derived SNPs, a second round of imputation is performed after removing genotyped SNPs with low empirical R2 (ER2 < 0.9, step 6, Supplementary Fig. 1). Finally, following association testing (step 7), filtering based on MAF ( > 0.01), imputation quality (R2 > 0.8), and imputation quality difference between cases (i.e., array data) and controls (i.e., WGS data) is step 8 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$|{R}_{{array}}^{2}-{R}_{{WGS}}^{2}|\, < \,0.1$$\end{document}∣Rarray2−RWGS2∣<0.1, Supplementary Fig. 2) which minimizes technical variation in the combined case/control data. More details regarding the development of the protocol can be found in the “Protocol Development” section of Methods.