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GWAS Study

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

de Vries PS, Sabater-Lleal M, Chasman DI et al.

28107422 PubMed ID
GWAS Study Type
91953 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

DV
de Vries PS
SM
Sabater-Lleal M
CD
Chasman DI
TS
Trompet S
AT
Ahluwalia TS
TA
Teumer A
KM
Kleber ME
CM
Chen MH
WJ
Wang JJ
AJ
Attia JR
MR
Marioni RE
SM
Steri M
WL
Weng LC
PR
Pool R
GV
Grossmann V
BJ
Brody JA
VC
Venturini C
TT
Tanaka T
RL
Rose LM
OC
Oldmeadow C
MJ
Mazur J
BS
Basu S
FM
Frånberg M
YQ
Yang Q
LS
Ligthart S
HJ
Hottenga JJ
RA
Rumley A
MA
Mulas A
DC
de Craen AJ
GA
Grotevendt A
TK
Taylor KD
DG
Delgado GE
KA
Kifley A
LL
Lopez LM
BT
Berentzen TL
MM
Mangino M
BS
Bandinelli S
MA
Morrison AC
HA
Hamsten A
TG
Tofler G
DM
de Maat MP
DH
Draisma HH
LG
Lowe GD
ZM
Zoledziewska M
SN
Sattar N
LK
Lackner KJ
VU
Völker U
MB
McKnight B
HJ
Huang J
HE
Holliday EG
MM
McEvoy MA
SJ
Starr JM
HP
Hysi PG
HD
Hernandez DG
GW
Guan W
RF
Rivadeneira F
MW
McArdle WL
SP
Slagboom PE
ZT
Zeller T
PB
Psaty BM
UA
Uitterlinden AG
DG
de Geus EJ
SD
Stott DJ
BH
Binder H
HA
Hofman A
FO
Franco OH
RJ
Rotter JI
FL
Ferrucci L
ST
Spector TD
DI
Deary IJ
MW
März W
GA
Greinacher A
WP
Wild PS
CF
Cucca F
BD
Boomsma DI
WH
Watkins H
TW
Tang W
RP
Ridker PM
JJ
Jukema JW
SR
Scott RJ
MP
Mitchell P
HT
Hansen T
OC
O'Donnell CJ
SN
Smith NL
SD
Strachan DP
DA
Dehghan A
Chapter II

Abstract

Summary of the research findings

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.

91,953 European ancestry individuals (imputed to HapMap)

Chapter III

Study Statistics

Key metrics and study information

91953
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
Sweden, U.S., Australia, Italy, Netherlands, Germany, U.K., Republic of Ireland, Denmark
Recruitment Country
Chapter IV

Analysis

Comprehensive review of health and genetic findings

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Analysis In Progress

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