The Effect of Haplotype-Block Definitions on Inference of Haplotype-Block Structure and htSNPs Selection

It has been recently suggested that the human genome is organized as a series of haplotype blocks, and efforts to create a genome-wide haplotype map are already underway. Several computational algorithms have been proposed to partition the genome. However, little is known about their behaviors in relation to the haplotype-block partitioning and haplotype-tagging SNPs selection. Here, we present a systematic comparison of three classes of haplotype-block partition definitions, a diversity-based method, a linkage-disequilibrium (LD)-based method, and a recombination-based method. The data used were derived from a coalescent simulation under both a uniform recombination model and one that assumes recombination hotspots. There were considerable differences in haplotype information loss in the measure of entropy when the partition methods were compared under different population-genetics scenarios. Under both recombination models, the results from the LD-based definition and the recombination-based definition were more similar to each other than were the results from the diversity-based definition. This work demonstrates that when undertaking haplotype-based association mapping, the choice of haplotype-block definition and SNP selection requires careful consideration.