MBE Advance Access published online on September 15, 2004
Molecular Biology and Evolution, doi:10.1093/molbev/msh266
Molecular Biology and Evolution © Society for Molecular Biology and Evolution 2004; all rights reserved
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1 National Laboratory of Medical Molecular Biology; Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100005, People's Republic of China; Chinese National Human Genome Center, Beijing 100176, People's Republic of China
* To whom correspondence should be addressed. E-mail: sheny{at}ms.imicams.ac.cn.
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 (the International HapMap project). 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 genetic scenarios. Under both recombination models, the results from the LD-based definition and the recombination-based definition were more similar to each other than 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.
Research Article
The Effect of Haplotype Block Definitions on Inference of Haplotype Block Structure and htSNPs Selection
2 Chinese National Human Genome Center, Beijing 100176, People's Republic of China; SGDP, Institute of Psychiatry, Kings College, Denmark Hill, London, United Kingdom
3 MOE Key Laboratory of Bioinformatics, Department of Automation, Tsinghua University, Beijing 100084, People's Republic of China
4 SGDP, Institute of Psychiatry, Kings College, Denmark Hill, London, United Kingdom
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