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Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies
During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436888/ https://www.ncbi.nlm.nih.gov/pubmed/22970228 http://dx.doi.org/10.1371/journal.pone.0044483 |
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author | Hong, Huixiao Xu, Lei Liu, Jie Jones, Wendell D. Su, Zhenqiang Ning, Baitang Perkins, Roger Ge, Weigong Miclaus, Kelci Zhang, Li Park, Kyunghee Green, Bridgett Han, Tao Fang, Hong Lambert, Christophe G. Vega, Silvia C. Lin, Simon M. Jafari, Nadereh Czika, Wendy Wolfinger, Russell D. Goodsaid, Federico Tong, Weida Shi, Leming |
author_facet | Hong, Huixiao Xu, Lei Liu, Jie Jones, Wendell D. Su, Zhenqiang Ning, Baitang Perkins, Roger Ge, Weigong Miclaus, Kelci Zhang, Li Park, Kyunghee Green, Bridgett Han, Tao Fang, Hong Lambert, Christophe G. Vega, Silvia C. Lin, Simon M. Jafari, Nadereh Czika, Wendy Wolfinger, Russell D. Goodsaid, Federico Tong, Weida Shi, Leming |
author_sort | Hong, Huixiao |
collection | PubMed |
description | During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors. High reliability of genotyping technology is needed to have confidence in using SNP data and interpreting GWAS results. Therefore, reproducibility of two widely genotyping technology platforms from Affymetrix and Illumina was assessed by analyzing four technical replicates from each of the six individuals in five laboratories. Genotype concordance of 99.40% to 99.87% within a laboratory for the sample platform, 98.59% to 99.86% across laboratories for the same platform, and 98.80% across genotyping platforms was observed. Moreover, arrays with low quality data were detected when comparing genotyping data from technical replicates, but they could not be detected according to venders’ quality control (QC) suggestions. Our results demonstrated the technical reliability of currently available genotyping platforms but also indicated the importance of incorporating some technical replicates for genotyping QC in order to improve the reliability of GWAS results. The impact of discordant genotypes on association analysis results was simulated and could explain, at least in part, the irreproducibility of some GWAS findings when the effect size (i.e. the odds ratio) and the minor allele frequencies are low. |
format | Online Article Text |
id | pubmed-3436888 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34368882012-09-11 Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies Hong, Huixiao Xu, Lei Liu, Jie Jones, Wendell D. Su, Zhenqiang Ning, Baitang Perkins, Roger Ge, Weigong Miclaus, Kelci Zhang, Li Park, Kyunghee Green, Bridgett Han, Tao Fang, Hong Lambert, Christophe G. Vega, Silvia C. Lin, Simon M. Jafari, Nadereh Czika, Wendy Wolfinger, Russell D. Goodsaid, Federico Tong, Weida Shi, Leming PLoS One Research Article During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors. High reliability of genotyping technology is needed to have confidence in using SNP data and interpreting GWAS results. Therefore, reproducibility of two widely genotyping technology platforms from Affymetrix and Illumina was assessed by analyzing four technical replicates from each of the six individuals in five laboratories. Genotype concordance of 99.40% to 99.87% within a laboratory for the sample platform, 98.59% to 99.86% across laboratories for the same platform, and 98.80% across genotyping platforms was observed. Moreover, arrays with low quality data were detected when comparing genotyping data from technical replicates, but they could not be detected according to venders’ quality control (QC) suggestions. Our results demonstrated the technical reliability of currently available genotyping platforms but also indicated the importance of incorporating some technical replicates for genotyping QC in order to improve the reliability of GWAS results. The impact of discordant genotypes on association analysis results was simulated and could explain, at least in part, the irreproducibility of some GWAS findings when the effect size (i.e. the odds ratio) and the minor allele frequencies are low. Public Library of Science 2012-09-07 /pmc/articles/PMC3436888/ /pubmed/22970228 http://dx.doi.org/10.1371/journal.pone.0044483 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article Hong, Huixiao Xu, Lei Liu, Jie Jones, Wendell D. Su, Zhenqiang Ning, Baitang Perkins, Roger Ge, Weigong Miclaus, Kelci Zhang, Li Park, Kyunghee Green, Bridgett Han, Tao Fang, Hong Lambert, Christophe G. Vega, Silvia C. Lin, Simon M. Jafari, Nadereh Czika, Wendy Wolfinger, Russell D. Goodsaid, Federico Tong, Weida Shi, Leming Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies |
title | Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies |
title_full | Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies |
title_fullStr | Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies |
title_full_unstemmed | Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies |
title_short | Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies |
title_sort | technical reproducibility of genotyping snp arrays used in genome-wide association studies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436888/ https://www.ncbi.nlm.nih.gov/pubmed/22970228 http://dx.doi.org/10.1371/journal.pone.0044483 |
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