A Generalized Sequential Bonferroni Procedure for GWAS in Admixed Populations Incorporating Admixture Mapping Information into Association Tests.

Pubmed ID: 26087776

Pubmed Central ID: PMC4821476

Journal: Human heredity

Publication Date: Jan. 1, 2015

MeSH Terms: Humans, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Computer Simulation, Atherosclerosis, Models, Genetic, Chromosome Mapping, Linkage Disequilibrium, Black or African American

Grants: HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, HHSN268201100012C, 268201100011C, 268201100005C, 268201100007C, 268201100012C, 268201100009C, 268201100006C, 268201100010C, 2682011 00008C, R01GM081488, R01GM073766, R01 GM073766, UL1TR000058, UL1 TR000058, U01 HL101064, R01 HD060913, R01 GM081488, U01HL101064, HHSN268201100009I, HHSN268201100005G, HHSN268201100008I, HHSN268201100011I, HHSN268201100005I, HHSN268201100007I

Authors: Chen W, Chen X, Ren C, Qin H, Archer KJ, Ouyang W, Liu N, Luo X, Zhu X, Sun S, Gao G

Cite As: Chen W, Ren C, Qin H, Archer KJ, Ouyang W, Liu N, Chen X, Luo X, Zhu X, Sun S, Gao G. A Generalized Sequential Bonferroni Procedure for GWAS in Admixed Populations Incorporating Admixture Mapping Information into Association Tests. Hum Hered 2015;79(2):80-92. Epub 2015 Jun 13.

Studies:

Abstract

OBJECTIVE: To develop effective methods for GWAS in admixed populations such as African Americans. METHODS: We show that, when testing the null hypothesis that the test SNP is not in background linkage disequilibrium with the causal variants, several existing methods cannot control well the family-wise error rate (FWER) in the strong sense in GWAS. These existing methods include association tests adjusting for global ancestry and joint association tests that combine statistics from admixture mapping tests and association tests that correct for local ancestry. Furthermore, we describe a generalized sequential Bonferroni (smooth-GSB) procedure for GWAS that incorporates smoothed weights calculated from admixture mapping tests into association tests that correct for local ancestry. We have applied the smooth-GSB procedure to analyses of GWAS data on American Africans from the Atherosclerosis Risk in Communities (ARIC) Study. RESULTS: Our simulation studies indicate that the smooth-GSB procedure not only control the FWER, but also improves statistical power compared with association tests correcting for local ancestry. CONCLUSION: The smooth-GSB procedure can result in a better performance than several existing methods for GWAS in admixed populations.