Genome-wide association analysis of rheumatoid arthritis data via haplotype sharing.
We present computationally simple association tests based on haplotype sharing that can be easily applied to genome-wide association studies, while allowing use of fast (but not likelihood-based) haplotyping algorithms, and properly accounting for the uncertainty introduced by using inferred haplotypes. We also give haplotype sharing analyses that adjust for population stratification. We apply our methods to a genome-wide association study of rheumatoid arthritis available as Problem 1 of Genetic Analysis Workshop 16. In addition to the HLA region on chromosome 6, we find genome-wide significant signals at 7q33 and 13q31.3. These regions contain genes with interesting potential connections with rheumatoid arthritis and are not identified using single single-nucleotide polymorphism methods.
Allen
Andrew S
AS
Department of Biostatistics and Bioinformatics and Duke Clinical Research Institute, Duke University, DUMC 3850, Durham, North Carolina 27710 USA. andrew.s.allen@duke.edu.
Satten
Glen A
GA