Shim Heejung, Chun Hyonho, Engelman Corinne D, Payseur Bret A
Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, Wisconsin 53706 USA.
Department of Population Health Sciences, University of Wisconsin-Madison, 707 WARF Building, 610 North Walnut Street, Madison, Wisconsin 53726 USA.
BMC Proc. 2009 Dec 15;3 Suppl 7(Suppl 7):S35. doi: 10.1186/1753-6561-3-s7-s35.
The high genomic density of the single-nucleotide polymorphism (SNP) sets that are typically surveyed in genome-wide association studies (GWAS) now allows the application of haplotype-based methods. Although the choice of haplotype-based vs. individual-SNP approaches is expected to affect the results of association studies, few empirical comparisons of method performance have been reported on the genome-wide scale in the same set of individuals. To measure the relative ability of the two strategies to detect associations, we used a large dataset from the North American Rheumatoid Arthritis Consortium to: 1) partition the genome into haplotype blocks, 2) associate haplotypes with disease, and 3) compare the results with individual-SNP association mapping. Although some associations were shared across methods, each approach uniquely identified several strong candidate regions. Our results suggest that the application of both haplotype-based and individual-SNP testing to GWAS should be adopted as a routine procedure.
在全基因组关联研究(GWAS)中通常检测的单核苷酸多态性(SNP)集具有很高的基因组密度,这使得基于单倍型的方法得以应用。尽管基于单倍型的方法与单个SNP方法的选择预计会影响关联研究的结果,但在全基因组规模上,针对同一组个体的方法性能的实证比较报道较少。为了衡量这两种策略检测关联的相对能力,我们使用了来自北美类风湿性关节炎联盟的一个大型数据集来:1)将基因组划分为单倍型块,2)将单倍型与疾病关联,3)将结果与单个SNP关联图谱进行比较。尽管有些关联在不同方法中是共享的,但每种方法都独特地识别出了几个强候选区域。我们的结果表明,在GWAS中应将基于单倍型的检测和单个SNP检测作为常规程序采用。