Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, S-171 77 Stockholm, Sweden.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S74. doi: 10.1186/1471-2156-6-S1-S74.
Both haplotype-based and locus-based methods have been proposed as the most powerful methods to employ when fine mapping by association. Although haplotype-based methods utilize more information, they may lose power as a result of overparameterization, given the large number of haplotypes possible over even a few loci. Recently methods have been developed that cluster haplotypes with similar structure in the hope that this reflects shared genealogical ancestry. The aim is to reduce the number of parameters while retaining the genotype information relating to disease susceptibility. We have compared several haplotype-based methods with locus-based methods. We utilized 2 regions (D2 and D4) simulated to be in linkage disequilibrium and to be associated with disease susceptibility, combining 5 replicates at a time to produce 4 datasets that were analyzed. We found little difference in the performance of the haplotype-based methods and the locus-based methods in this dataset.
基于单体型和基于位点的方法都已被提出,作为通过关联进行精细映射时最有效的方法。虽然基于单体型的方法利用了更多的信息,但由于即使在几个位点上也可能存在大量的单体型,因此可能会由于过度参数化而失去效力。最近开发了一些方法,这些方法将具有相似结构的单体型聚类在一起,希望这反映了共同的谱系祖先。其目的是在保留与疾病易感性相关的基因型信息的同时,减少参数的数量。我们比较了几种基于单体型的方法和基于位点的方法。我们利用了 2 个模拟处于连锁不平衡并与疾病易感性相关的区域(D2 和 D4),每次结合 5 个重复,生成了 4 个数据集进行分析。我们发现,在这个数据集里,基于单体型的方法和基于位点的方法的性能差异不大。