The International HapMap Project and high- throughput genotyping technology have generated millions of genome-wide marker data that can be used in genetic studies. Each marker can be analyzed separately. But analyzing multiple markers simultaneously through haplotypes has generated great interest recently. Understanding the haplotype structure in the human genome may provide important information on human evolutionary history and identification of genetic variants responsible for human complex diseases. Since the alleles at closely linked markers on a single chromosome are often in statistical dependence (i.e. linkage disequilibrium (LD)), one crucial aspect of haplotype analysis is to characterize LD patterns in different regions and different populations. To assess the extent of correlation of genetic variation at multiple markers in a given region and a population, pairwise LD measures such as and have been commonly used. However, pairwise LD measures alone may be suboptimal to effectively capture the variability of background levels of disequilibrium since multilocus LD measures can provide information about simultaneous allele associations among multiple loci which pairwise LD measures miss. In addition, in order to fully characterize the haplotype structure and LD pattern at multiple markers, it is necessary to consider high order disequilibria and estimate their values.
|Date||30 March 2008|
|Contributors||Zhao-Bang Zeng, Jung-Ying Tzeng, Gregory Gibson, Philip Awadalla|
|Source Sets||North Carolina State University|
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