04941nas a2201165 4500008004100000022001400041245010700055210006900162260000900231300001300240490000700253520165900260100002201919700002501941700002301966700002001989700002802009700002202037700002202059700002002081700001902101700001902120700002502139700002202164700001802186700001502204700002002219700002302239700002402262700002002286700001902306700002702325700001902352700001702371700002302388700001602411700002002427700002302447700001602470700002102486700002502507700002102532700002002553700002502573700002002598700002002618700002302638700002102661700002502682700002402707700002002731700002102751700002502772700002502797700002002822700002802842700001902870700002102889700001702910700002202927700001502949700002702964700002002991700001903011700001903030700002303049700001703072700002603089700002203115700002003137700001803157700002003175700002803195700001903223700002003242700001903262700001903281700002103300700002203321700002003343700002003363700001803383700002003401700002403421700002103445700002103466700002303487700001803510700001803528700002003546700001903566700002103585700001903606700001903625700003003644700002303674700002303697700001903720856003603739 2017 eng d a1932-620300aComparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study.0 aComparison of HapMap and 1000 Genomes Reference Panels in a Larg c2017 ae01677420 v123 a
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.
1 ade Vries, Paul, S1 aSabater-Lleal, Maria1 aChasman, Daniel, I1 aTrompet, Stella1 aAhluwalia, Tarunveer, S1 aTeumer, Alexander1 aKleber, Marcus, E1 aChen, Ming-Huei1 aWang, Jie, Jin1 aAttia, John, R1 aMarioni, Riccardo, E1 aSteri, Maristella1 aWeng, Lu-Chen1 aPool, Rene1 aGrossmann, Vera1 aBrody, Jennifer, A1 aVenturini, Cristina1 aTanaka, Toshiko1 aRose, Lynda, M1 aOldmeadow, Christopher1 aMazur, Johanna1 aBasu, Saonli1 aFrånberg, Mattias1 aYang, Qiong1 aLigthart, Symen1 aHottenga, Jouke, J1 aRumley, Ann1 aMulas, Antonella1 ade Craen, Anton, J M1 aGrotevendt, Anne1 aTaylor, Kent, D1 aDelgado, Graciela, E1 aKifley, Annette1 aLopez, Lorna, M1 aBerentzen, Tina, L1 aMangino, Massimo1 aBandinelli, Stefania1 aMorrison, Alanna, C1 aHamsten, Anders1 aTofler, Geoffrey1 ade Maat, Moniek, P M1 aDraisma, Harmen, H M1 aLowe, Gordon, D1 aZoledziewska, Magdalena1 aSattar, Naveed1 aLackner, Karl, J1 aVölker, Uwe1 aMcKnight, Barbara1 aHuang, Jie1 aHolliday, Elizabeth, G1 aMcEvoy, Mark, A1 aStarr, John, M1 aHysi, Pirro, G1 aHernandez, Dena, G1 aGuan, Weihua1 aRivadeneira, Fernando1 aMcArdle, Wendy, L1 aSlagboom, Eline1 aZeller, Tanja1 aPsaty, Bruce, M1 aUitterlinden, André, G1 aGeus, Eco, J C1 aStott, David, J1 aBinder, Harald1 aHofman, Albert1 aFranco, Oscar, H1 aRotter, Jerome, I1 aFerrucci, Luigi1 aSpector, Tim, D1 aDeary, Ian, J1 aMärz, Winfried1 aGreinacher, Andreas1 aWild, Philipp, S1 aCucca, Francesco1 aBoomsma, Dorret, I1 aWatkins, Hugh1 aTang, Weihong1 aRidker, Paul, M1 aJukema, Jan, W1 aScott, Rodney, J1 aMitchell, Paul1 aHansen, Torben1 aO'Donnell, Christopher, J1 aSmith, Nicholas, L1 aStrachan, David, P1 aDehghan, Abbas uhttps://chs-nhlbi.org/node/7343