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    Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study


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    Yao, Yong-Gang, 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. and Dehghan, Abbas (2017) Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study. PLoS ONE, 12 (1). pp. 1-22. ISSN 1932-6203

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    Abstract

    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.
    Item Type: Article
    Keywords: Comparison; HapMap; 1000 Genomes; Reference Panels; Large-Scale; Genome-Wide; Association Study;
    Academic Unit: Faculty of Science and Engineering > Biology
    Faculty of Science and Engineering > Research Institutes > Human Health Institute
    Item ID: 17194
    Identification Number: 10.1371/journal.pone.0167742
    Depositing User: Lorna Lopez
    Date Deposited: 17 May 2023 09:52
    Journal or Publication Title: PLoS ONE
    Publisher: Public Library of Science
    Refereed: Yes
    Related URLs:
    URI: https://mural.maynoothuniversity.ie/id/eprint/17194
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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