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Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study
An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In or...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5249120/ https://www.ncbi.nlm.nih.gov/pubmed/28107422 http://dx.doi.org/10.1371/journal.pone.0167742 |
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author | de Vries, Paul S. Sabater-Lleal, Maria Chasman, Daniel I. Trompet, Stella Ahluwalia, Tarunveer S. Teumer, Alexander Kleber, Marcus E. Chen, Ming-Huei Wang, Jie Jin Attia, John R. Marioni, Riccardo E. Steri, Maristella Weng, Lu-Chen Pool, Rene Grossmann, Vera Brody, Jennifer A. Venturini, Cristina Tanaka, Toshiko Rose, Lynda M. Oldmeadow, Christopher Mazur, Johanna Basu, Saonli Frånberg, Mattias Yang, Qiong Ligthart, Symen Hottenga, Jouke J. Rumley, Ann Mulas, Antonella de Craen, Anton J. M. Grotevendt, Anne Taylor, Kent D. Delgado, Graciela E. Kifley, Annette Lopez, Lorna M. Berentzen, Tina L. Mangino, Massimo Bandinelli, Stefania Morrison, Alanna C. Hamsten, Anders Tofler, Geoffrey de Maat, Moniek P. M. Draisma, Harmen H. M. Lowe, Gordon D. Zoledziewska, Magdalena Sattar, Naveed Lackner, Karl J. Völker, Uwe McKnight, Barbara Huang, Jie Holliday, Elizabeth G. McEvoy, Mark A. Starr, John M. Hysi, Pirro G. Hernandez, Dena G. Guan, Weihua Rivadeneira, Fernando McArdle, Wendy L. Slagboom, P. Eline Zeller, Tanja Psaty, Bruce M. Uitterlinden, André G. de Geus, Eco J. C. Stott, David J. Binder, Harald Hofman, Albert Franco, Oscar H. Rotter, Jerome I. Ferrucci, Luigi Spector, Tim D. Deary, Ian J. März, Winfried Greinacher, Andreas Wild, Philipp S. Cucca, Francesco Boomsma, Dorret I. Watkins, Hugh Tang, Weihong Ridker, Paul M. Jukema, Jan W. Scott, Rodney J. Mitchell, Paul Hansen, Torben O'Donnell, Christopher J. Smith, Nicholas L. Strachan, David P. Dehghan, Abbas |
author_facet | de Vries, Paul S. Sabater-Lleal, Maria Chasman, Daniel I. Trompet, Stella Ahluwalia, Tarunveer S. Teumer, Alexander Kleber, Marcus E. Chen, Ming-Huei Wang, Jie Jin Attia, John R. Marioni, Riccardo E. Steri, Maristella Weng, Lu-Chen Pool, Rene Grossmann, Vera Brody, Jennifer A. Venturini, Cristina Tanaka, Toshiko Rose, Lynda M. Oldmeadow, Christopher Mazur, Johanna Basu, Saonli Frånberg, Mattias Yang, Qiong Ligthart, Symen Hottenga, Jouke J. Rumley, Ann Mulas, Antonella de Craen, Anton J. M. Grotevendt, Anne Taylor, Kent D. Delgado, Graciela E. Kifley, Annette Lopez, Lorna M. Berentzen, Tina L. Mangino, Massimo Bandinelli, Stefania Morrison, Alanna C. Hamsten, Anders Tofler, Geoffrey de Maat, Moniek P. M. Draisma, Harmen H. M. Lowe, Gordon D. Zoledziewska, Magdalena Sattar, Naveed Lackner, Karl J. Völker, Uwe McKnight, Barbara Huang, Jie Holliday, Elizabeth G. McEvoy, Mark A. Starr, John M. Hysi, Pirro G. Hernandez, Dena G. Guan, Weihua Rivadeneira, Fernando McArdle, Wendy L. Slagboom, P. Eline Zeller, Tanja Psaty, Bruce M. Uitterlinden, André G. de Geus, Eco J. C. Stott, David J. Binder, Harald Hofman, Albert Franco, Oscar H. Rotter, Jerome I. Ferrucci, Luigi Spector, Tim D. Deary, Ian J. März, Winfried Greinacher, Andreas Wild, Philipp S. Cucca, Francesco Boomsma, Dorret I. Watkins, Hugh Tang, Weihong Ridker, Paul M. Jukema, Jan W. Scott, Rodney J. Mitchell, Paul Hansen, Torben O'Donnell, Christopher J. Smith, Nicholas L. Strachan, David P. Dehghan, Abbas |
author_sort | de Vries, Paul S. |
collection | PubMed |
description | An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10(−8) is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10(−8)), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development. |
format | Online Article Text |
id | pubmed-5249120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-52491202017-02-06 Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study de Vries, Paul S. Sabater-Lleal, Maria Chasman, Daniel I. Trompet, Stella Ahluwalia, Tarunveer S. Teumer, Alexander Kleber, Marcus E. Chen, Ming-Huei Wang, Jie Jin Attia, John R. Marioni, Riccardo E. Steri, Maristella Weng, Lu-Chen Pool, Rene Grossmann, Vera Brody, Jennifer A. Venturini, Cristina Tanaka, Toshiko Rose, Lynda M. Oldmeadow, Christopher Mazur, Johanna Basu, Saonli Frånberg, Mattias Yang, Qiong Ligthart, Symen Hottenga, Jouke J. Rumley, Ann Mulas, Antonella de Craen, Anton J. M. Grotevendt, Anne Taylor, Kent D. Delgado, Graciela E. Kifley, Annette Lopez, Lorna M. Berentzen, Tina L. Mangino, Massimo Bandinelli, Stefania Morrison, Alanna C. Hamsten, Anders Tofler, Geoffrey de Maat, Moniek P. M. Draisma, Harmen H. M. Lowe, Gordon D. Zoledziewska, Magdalena Sattar, Naveed Lackner, Karl J. Völker, Uwe McKnight, Barbara Huang, Jie Holliday, Elizabeth G. McEvoy, Mark A. Starr, John M. Hysi, Pirro G. Hernandez, Dena G. Guan, Weihua Rivadeneira, Fernando McArdle, Wendy L. Slagboom, P. Eline Zeller, Tanja Psaty, Bruce M. Uitterlinden, André G. de Geus, Eco J. C. Stott, David J. Binder, Harald Hofman, Albert Franco, Oscar H. Rotter, Jerome I. Ferrucci, Luigi Spector, Tim D. Deary, Ian J. März, Winfried Greinacher, Andreas Wild, Philipp S. Cucca, Francesco Boomsma, Dorret I. Watkins, Hugh Tang, Weihong Ridker, Paul M. Jukema, Jan W. Scott, Rodney J. Mitchell, Paul Hansen, Torben O'Donnell, Christopher J. Smith, Nicholas L. Strachan, David P. Dehghan, Abbas PLoS One Research Article An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10(−8) is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10(−8)), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development. Public Library of Science 2017-01-20 /pmc/articles/PMC5249120/ /pubmed/28107422 http://dx.doi.org/10.1371/journal.pone.0167742 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article de Vries, Paul S. Sabater-Lleal, Maria Chasman, Daniel I. Trompet, Stella Ahluwalia, Tarunveer S. Teumer, Alexander Kleber, Marcus E. Chen, Ming-Huei Wang, Jie Jin Attia, John R. Marioni, Riccardo E. Steri, Maristella Weng, Lu-Chen Pool, Rene Grossmann, Vera Brody, Jennifer A. Venturini, Cristina Tanaka, Toshiko Rose, Lynda M. Oldmeadow, Christopher Mazur, Johanna Basu, Saonli Frånberg, Mattias Yang, Qiong Ligthart, Symen Hottenga, Jouke J. Rumley, Ann Mulas, Antonella de Craen, Anton J. M. Grotevendt, Anne Taylor, Kent D. Delgado, Graciela E. Kifley, Annette Lopez, Lorna M. Berentzen, Tina L. Mangino, Massimo Bandinelli, Stefania Morrison, Alanna C. Hamsten, Anders Tofler, Geoffrey de Maat, Moniek P. M. Draisma, Harmen H. M. Lowe, Gordon D. Zoledziewska, Magdalena Sattar, Naveed Lackner, Karl J. Völker, Uwe McKnight, Barbara Huang, Jie Holliday, Elizabeth G. McEvoy, Mark A. Starr, John M. Hysi, Pirro G. Hernandez, Dena G. Guan, Weihua Rivadeneira, Fernando McArdle, Wendy L. Slagboom, P. Eline Zeller, Tanja Psaty, Bruce M. Uitterlinden, André G. de Geus, Eco J. C. Stott, David J. Binder, Harald Hofman, Albert Franco, Oscar H. Rotter, Jerome I. Ferrucci, Luigi Spector, Tim D. Deary, Ian J. März, Winfried Greinacher, Andreas Wild, Philipp S. Cucca, Francesco Boomsma, Dorret I. Watkins, Hugh Tang, Weihong Ridker, Paul M. Jukema, Jan W. Scott, Rodney J. Mitchell, Paul Hansen, Torben O'Donnell, Christopher J. Smith, Nicholas L. Strachan, David P. Dehghan, Abbas Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study |
title | Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study |
title_full | Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study |
title_fullStr | Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study |
title_full_unstemmed | Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study |
title_short | Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study |
title_sort | comparison of hapmap and 1000 genomes reference panels in a large-scale genome-wide association study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5249120/ https://www.ncbi.nlm.nih.gov/pubmed/28107422 http://dx.doi.org/10.1371/journal.pone.0167742 |
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