The effect of genome-wide association scan quality control on imputation outcome for common variants

Lorraine Southam; Kalliope Panoutsopoulou; N. William Rayner; Kay Chapman; Caroline Durrant; Teresa Ferreira; Nigel Arden; Andrew Carr; Panos Deloukas; Michael Doherty; John Loughlin; Andrew McCaskie; William E. R. Ollier; Stuart Ralston; Timothy D. Spector; Ana M. Valdes; Gillian A. Wallis; J. Mark Wilkinson; Jonathan Marchini; Eleftheria Zeggini

doi:10.1038/ejhg.2010.242

The effect of genome-wide association scan quality control on imputation outcome for common variants

Lorraine Southam, Kalliope Panoutsopoulou, N. William Rayner, Kay Chapman, Caroline Durrant, Teresa Ferreira, Nigel Arden, Andrew Carr, Panos Deloukas, Michael Doherty, John Loughlin, Andrew McCaskie, William E. R. Ollier, Stuart Ralston, Timothy D. Spector, Ana M. Valdes, Gillian A. Wallis, J. Mark Wilkinson, Jonathan Marchini, Eleftheria Zeggini

Research output: Contribution to journal › Article › peer-review

25 Citations (Scopus)

Abstract

Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWASs). Directly typed SNP quality control (QC) is thought to affect imputation quality. It is, therefore, common practise to use quality-controlled (QCed) data as an 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 3177 samples with Illumina 610k (Illumina, San Diego, CA, USA) GWAS data, applying different QC steps each time. The imputed genotypes were compared with 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 generalise to the imputation of low frequency and rare variants. European Journal of Human Genetics (2011) 19, 610-614; doi:10.1038/ejhg.2010.242; published online 26 January 2011

Original language	English
Pages (from-to)	610 - 614
Number of pages	5
Journal	European Journal of Human Genetics
Volume	19
Issue number	5
DOIs	https://doi.org/10.1038/ejhg.2010.242
Publication status	Published - May 2011

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Southam, L., Panoutsopoulou, K., Rayner, N. W., Chapman, K., Durrant, C., Ferreira, T., Arden, N., Carr, A., Deloukas, P., Doherty, M., Loughlin, J., McCaskie, A., Ollier, W. E. R., Ralston, S., Spector, T. D., Valdes, A. M., Wallis, G. A., Wilkinson, J. M., Marchini, J., & Zeggini, E. (2011). The effect of genome-wide association scan quality control on imputation outcome for common variants. European Journal of Human Genetics, 19(5), 610 - 614. https://doi.org/10.1038/ejhg.2010.242

@article{7062dae2458246f1bcc4b4bcc3d0dfac,

title = "The effect of genome-wide association scan quality control on imputation outcome for common variants",

abstract = "Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWASs). Directly typed SNP quality control (QC) is thought to affect imputation quality. It is, therefore, common practise to use quality-controlled (QCed) data as an 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 3177 samples with Illumina 610k (Illumina, San Diego, CA, USA) GWAS data, applying different QC steps each time. The imputed genotypes were compared with 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 generalise to the imputation of low frequency and rare variants. European Journal of Human Genetics (2011) 19, 610-614; doi:10.1038/ejhg.2010.242; published online 26 January 2011",

author = "Lorraine Southam and Kalliope Panoutsopoulou and Rayner, {N. William} and Kay Chapman and Caroline Durrant and Teresa Ferreira and Nigel Arden and Andrew Carr and Panos Deloukas and Michael Doherty and John Loughlin and Andrew McCaskie and Ollier, {William E. R.} and Stuart Ralston and Spector, {Timothy D.} and Valdes, {Ana M.} and Wallis, {Gillian A.} and Wilkinson, {J. Mark} and Jonathan Marchini and Eleftheria Zeggini",

year = "2011",

month = may,

doi = "10.1038/ejhg.2010.242",

language = "English",

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journal = "European Journal of Human Genetics",

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Southam, L, Panoutsopoulou, K, Rayner, NW, Chapman, K, Durrant, C, Ferreira, T, Arden, N, Carr, A, Deloukas, P, Doherty, M, Loughlin, J, McCaskie, A, Ollier, WER, Ralston, S, Spector, TD , Valdes, AM, Wallis, GA, Wilkinson, JM, Marchini, J & Zeggini, E 2011, 'The effect of genome-wide association scan quality control on imputation outcome for common variants', European Journal of Human Genetics, vol. 19, no. 5, pp. 610 - 614. https://doi.org/10.1038/ejhg.2010.242

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AU - Southam, Lorraine

AU - Panoutsopoulou, Kalliope

AU - Rayner, N. William

AU - Chapman, Kay

AU - Durrant, Caroline

AU - Ferreira, Teresa

AU - Arden, Nigel

AU - Carr, Andrew

AU - Deloukas, Panos

AU - Doherty, Michael

AU - Loughlin, John

AU - McCaskie, Andrew

AU - Ollier, William E. R.

AU - Ralston, Stuart

AU - Spector, Timothy D.

AU - Valdes, Ana M.

AU - Wallis, Gillian A.

AU - Wilkinson, J. Mark

AU - Marchini, Jonathan

AU - Zeggini, Eleftheria

PY - 2011/5

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N2 - Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWASs). Directly typed SNP quality control (QC) is thought to affect imputation quality. It is, therefore, common practise to use quality-controlled (QCed) data as an 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 3177 samples with Illumina 610k (Illumina, San Diego, CA, USA) GWAS data, applying different QC steps each time. The imputed genotypes were compared with 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 generalise to the imputation of low frequency and rare variants. European Journal of Human Genetics (2011) 19, 610-614; doi:10.1038/ejhg.2010.242; published online 26 January 2011

AB - Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWASs). Directly typed SNP quality control (QC) is thought to affect imputation quality. It is, therefore, common practise to use quality-controlled (QCed) data as an 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 3177 samples with Illumina 610k (Illumina, San Diego, CA, USA) GWAS data, applying different QC steps each time. The imputed genotypes were compared with 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 generalise to the imputation of low frequency and rare variants. European Journal of Human Genetics (2011) 19, 610-614; doi:10.1038/ejhg.2010.242; published online 26 January 2011

U2 - 10.1038/ejhg.2010.242

DO - 10.1038/ejhg.2010.242

M3 - Article

VL - 19

SP - 610

EP - 614

JO - European Journal of Human Genetics

JF - European Journal of Human Genetics

IS - 5

ER -

The effect of genome-wide association scan quality control on imputation outcome for common variants

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