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Public Library of Science, PLoS ONE, 1(12), p. e0167742, 2017

DOI: 10.1371/journal.pone.0167742

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

Journal article published in 2017 by P. S. (Paul) de Vries, Ps de Vries, Ajm de Craen, Ejc de Geus, M. (Maria) Sabater-Lleal, Di I. (Daniel) Chasman, S. (Stella) Trompet, Ts S. (Tarunveer Singh) Ahluwalia ORCID, A. (Alexander) Teumer ORCID, Me E. (Marcus) Kleber, M.-H. (Ming-Huei) Chen, Jj J. (Jie Jin) Wang, J. (John) Attia, Re E. (Riccardo) Marioni, M. (Maristella) Steri ORCID and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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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