title: Admixture mapping analysis in the context of GWAS with GAW18 data.
abstract: Admixture mapping is a disease-mapping strategy to identify disease susceptibility variants in an admixed population that is a result of mating between 2 historically separated populations differing in allele frequencies and disease prevalence. With the increasing availability of high-density genotyping data generated in genome-wide association studies, it is of interest to investigate how to apply admixture mapping in the context of the genome-wide association studies and how to adjust for admixture in association tests. In this study, we first evaluated 3 different local ancestry inference methods, LAMP, LAMP-LD, and MULTIMIX. Then we applied admixture mapping analysis based on estimated local ancestry. Finally, we performed association tests with adjustment for local ancestry.
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
authors.forename: Mengjie
authors.initials: M
authors.lastname: Chen
authors.affiliation: Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT 06520, USA.
authors.forename: Can
authors.initials: C
authors.lastname: Yang
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
authors.forename: Cong
authors.initials: C
authors.lastname: Li
authors.affiliation: Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT 06520, USA.
authors.forename: Lin
authors.initials: L
authors.lastname: Hou
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
authors.forename: Xiaowei
authors.initials: X
authors.lastname: Chen
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA ; Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT 06520, USA.
authors.forename: Hongyu
authors.initials: H
authors.lastname: Zhao