The effect of genome-wide association scan quality control on imputation outcome for common variants
Résumé
Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWAS). Directly-typed SNP quality control is thought to affect imputation quality. It is therefore common practice to use quality-controlled (QCed) data as input for imputing genotypes. This study aims to determine the effect of commonly-applied QC steps on imputation outcomes. We performed several iterations of imputing SNPs across chromosome 22 in a dataset consisting of 3,177 samples with Illumina 610k GWAS data, applying different QC steps each time. The imputed genotypes were compared to the directly-typed genotypes. In addition, we investigated the correlation between alternatively QCed data. We also applied a series of post-imputation QC steps balancing elimination of poorly-imputed SNPs and information loss. We found that the difference between the unQCed data and the fully-QCed data on imputation outcome was minimal. Our study shows that imputation of common variants is generally very accurate and robust to GWAS QC, which is not a major factor affecting imputation outcome. A minority of common-frequency SNPs with particular properties cannot be accurately imputed regardless of QC stringency. These findings may not generalize to the imputation of low frequency and rare variants.
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