Robust Association Tests for the Replication of Genome-Wide Association Studies.
In genome-wide association study (GWAS), robust genetic association tests such as maximum of three CATTs (MAX3), each corresponding to recessive, additive, and dominant genetic models, the minimum p value of Pearson's Chi-square test with 2 degrees of freedom, and CATT based on additive genetic model (MIN2), genetic model selection (GMS), and genetic model exclusion (GME) methods have been shown to provide better power performance under wide range of underlying genetic models. In this paper, we demonstrate how these robust tests can be applied to the replication study of GWAS and how the overall statistical significance can be evaluated using the combined test formed by p values of the discovery and replication studies.
Biometric Research Branch, Research Institute and Hospital, National Cancer Center, Gyeonggi-do, Goyang-si 410-769, Republic of Korea.
Jungnam
J
Joo
Department of Statistics, Dongguk University, Seoul 100-715, Republic of Korea.
Ju-Hyun
JH
Park
Biometric Research Branch, Research Institute and Hospital, National Cancer Center, Gyeonggi-do, Goyang-si 410-769, Republic of Korea.
Bora
B
Lee
Biometric Research Branch, Research Institute and Hospital, National Cancer Center, Gyeonggi-do, Goyang-si 410-769, Republic of Korea.
Boram
B
Park
Biometric Research Branch, Research Institute and Hospital, National Cancer Center, Gyeonggi-do, Goyang-si 410-769, Republic of Korea.
Sohee
S
Kim
Lung Cancer Branch, Research Institute and Hospital, National Cancer Center, Gyeonggi-do, Goyang-si 410-769, Republic of Korea.
Kyong-Ah
KA
Yoon
Lung Cancer Branch, Research Institute and Hospital, National Cancer Center, Gyeonggi-do, Goyang-si 410-769, Republic of Korea.
Jin Soo
JS
Lee
Office of Biostatistics Research, National Heart, Lung and Blood Institute, Bethesda, MD 20892-7938, USA.
Nancy L
NL
Geller
D004261:DNA Replication / Q000502:physiology*; D016678:Genome / Q000502:physiology*; D055106:Genome-Wide Association Study; D008957:Models, Genetic