title: Detecting local haplotype sharing and haplotype association.
abstract: A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype.org.
authors.affiliation: U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas 77030 Department of Biomedical Engineering, Southeast University, Nanjing, Jiangsu 210000, China.
authors.forename: Hanli
authors.initials: H
authors.lastname: Xu
authors.affiliation: U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas 77030 Department of Pediatrics, Baylor College of Medicine, Houston, Texas 77030 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030 yongtaog@bcm.edu.
authors.forename: Yongtao
authors.initials: Y
authors.lastname: Guan
mesh_terms: D000465:Algorithms; D000483:Alleles; D001499:Bayes Theorem; D016022:Case-Control Studies; D003198:Computer Simulation; D030541:Databases, Genetic; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D006239:Haplotypes / Q000235:genetics*; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics
keywords: LD; association; haplotype; local haplotype sharing; two-layer HMM