Title | Haplotype block linkage disequilibrium mapping. |
Publication Type | Journal Article |
Year of Publication | 2003 |
Authors | Xiong, M, Zhao, J, Boerwinkle, E |
Journal | Front Biosci |
Volume | 8 |
Pagination | a85-93 |
Date Published | 2003 May 01 |
ISSN | 1093-9946 |
Keywords | Chromosome Mapping, Genetic Markers, Genetics, Population, Haplotypes, Humans, Linkage Disequilibrium, Models, Genetic, Models, Statistical |
Abstract | Linkage disequilibrium (LD) mapping is emerging as a powerful alternative approach to identifying genes for complex disease. However, the feasibility and success of LD mapping depend largely on the extent and pattern of LD. Erratic pattern of pair-wise LD seriously compromises LD mapping. Recently discovered haplotype block structure dramatically alleviates the irregular pattern of LD and holds the promise for mapping complex disease genes. To facilitate applications of the haplotype block LD mapping, in this report we conduct theoretical analysis for haplotype block LD mapping. We present an overall LD measure of the haplotype to quantify the LD level of the haplotype block, between the haplotype blocks, and between the haplotype block and the marker locus. Most theoretical and empirical studies of the extent of LD and evaluation of the power of LD mapping have focused on pair-wise LD and single marker LD mapping. There is a lack of systematic and integrative analysis for the haplotype block LD mapping. In this report, we develop population genetic models of the haplotype blocks and analytic tools for calculation of noncentrality parameter of the statistic for the haplotype block LD mapping. We evaluate the impact of the population parameters and disease models on the power of the haplotype block LD mapping in the hope to improve its study design. We compare the powers of the single marker LD and haplotype block LD mapping. Haplotype block structure is an important discovery. Our preliminary results of theoretic analysis further demonstrate that the haplotype block LD analysis is a breakthrough in LD mapping and is a promising tool for genome-wide association studies.
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DOI | 10.2741/919 |
Alternate Journal | Front Biosci |
PubMed ID | 12700120 |