Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study
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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.
In: PLOS ONE, Vol. 12, No. 1, 2017, p. e0167742.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study
AU - de Vries, Paul S
AU - Sabater-Lleal, Maria
AU - Chasman, Daniel I
AU - Trompet, Stella
AU - Ahluwalia, Tarunveer S
AU - Teumer, Alexander
AU - Kleber, Marcus E
AU - Chen, Ming-Huei
AU - Wang, Jie Jin
AU - Attia, John R
AU - Marioni, Riccardo E
AU - Steri, Maristella
AU - Weng, Lu-Chen
AU - Pool, Rene
AU - Grossmann, Vera
AU - Brody, Jennifer A
AU - Venturini, Cristina
AU - Tanaka, Toshiko
AU - Rose, Lynda M
AU - Oldmeadow, Christopher
AU - Mazur, Johanna
AU - Basu, Saonli
AU - Frånberg, Mattias
AU - Yang, Qiong
AU - Ligthart, Symen
AU - Hottenga, Jouke J
AU - Rumley, Ann
AU - Mulas, Antonella
AU - de Craen, Anton J M
AU - Grotevendt, Anne
AU - Taylor, Kent D
AU - Delgado, Graciela E
AU - Kifley, Annette
AU - Lopez, Lorna M
AU - Berentzen, Tina L
AU - Mangino, Massimo
AU - Bandinelli, Stefania
AU - Morrison, Alanna C
AU - Hamsten, Anders
AU - Tofler, Geoffrey
AU - de Maat, Moniek P M
AU - Draisma, Harmen H M
AU - Lowe, Gordon D
AU - Zoledziewska, Magdalena
AU - Sattar, Naveed
AU - Lackner, Karl J
AU - Völker, Uwe
AU - McKnight, Barbara
AU - Huang, Jie
AU - Holliday, Elizabeth G
AU - McEvoy, Mark A
AU - Starr, John M
AU - Hysi, Pirro G
AU - Hernandez, Dena G
AU - Guan, Weihua
AU - Rivadeneira, Fernando
AU - McArdle, Wendy L
AU - Slagboom, P Eline
AU - Zeller, Tanja
AU - Psaty, Bruce M
AU - Uitterlinden, André G
AU - de Geus, Eco J C
AU - Stott, David J
AU - Binder, Harald
AU - Hofman, Albert
AU - Franco, Oscar H
AU - Rotter, Jerome I
AU - Ferrucci, Luigi
AU - Spector, Tim D
AU - Deary, Ian J
AU - März, Winfried
AU - Greinacher, Andreas
AU - Wild, Philipp S
AU - Cucca, Francesco
AU - Boomsma, Dorret I
AU - Watkins, Hugh
AU - Tang, Weihong
AU - Ridker, Paul M
AU - Jukema, Jan W
AU - Scott, Rodney J
AU - Mitchell, Paul
AU - Hansen, Torben
AU - O'Donnell, Christopher J
AU - Smith, Nicholas L
AU - Strachan, David P
AU - Dehghan, Abbas
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Genome-Wide Association Study
KW - HapMap Project
KW - Humans
U2 - 10.1371/journal.pone.0167742
DO - 10.1371/journal.pone.0167742
M3 - SCORING: Journal article
C2 - 28107422
VL - 12
SP - e0167742
JO - PLOS ONE
JF - PLOS ONE
SN - 1932-6203
IS - 1
ER -