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Chunk #34 — Methods — GAWMerge development — Imputation strategy

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GAWMerge expands GWAS sample size and diversity by combining array-based genotyping and whole-genome sequencing.
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smokers and no disease was being tested between the datasets. Without the ER2 filter, we found many false positives (Supplementary Fig. 1a) based around the variant on chromosome 10 (chr10:32370743, ER2 = 0.391, MAF = 0.068). We recommend removing such genotyped SNPs with ER2 < 0.9 from the analysis and re-running imputation without these variants included. With this and other low-quality variants removed, false positives were controlled (Supplementary Fig. 1b). With the ER2 filter of 0.9, we found that 81.1% of SNPs met this criterion (Supplementary Fig. 1c) and these removed SNPs were scattered across the genome (Supplementary Fig. 1d).