The construction of linkage disequilibrium maps and their application to association mapping of disease genes
The construction of linkage disequilibrium maps and their application to association mapping of disease genes
Success in association mapping of disease genes depends on knowledge of Linkage Disequilibrium (LD) structure in candidate regions. An LD map characterising such structures is constructed by making use of the Malecot model which describes the decline of LD with physical distance based on pairwise measures of association between SNPs. The HapMap project provides a valuable resource that can be used to construct genome-wide LD maps. However, the millions of SNPs in the HapMap data pose a heavy computational challenge. This difficulty can be resolved by excluding the very distant SNP pairs without losing map quality. Modern computational technology with parallel processing can be used to speed up the process of map construction. A composite likelihood approach employing LD maps for association mapping has successfully localised several causal variants. An application to Rheumatoid Arthritis (RA) is described here. This approach, utilising the genome-wide LD map, is very suitable for genome-wide association studies.
University of Southampton
Kuo, Tai-Yue
f16263d2-5b38-4012-aced-a22108cef183
2008
Kuo, Tai-Yue
f16263d2-5b38-4012-aced-a22108cef183
Kuo, Tai-Yue
(2008)
The construction of linkage disequilibrium maps and their application to association mapping of disease genes.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
Success in association mapping of disease genes depends on knowledge of Linkage Disequilibrium (LD) structure in candidate regions. An LD map characterising such structures is constructed by making use of the Malecot model which describes the decline of LD with physical distance based on pairwise measures of association between SNPs. The HapMap project provides a valuable resource that can be used to construct genome-wide LD maps. However, the millions of SNPs in the HapMap data pose a heavy computational challenge. This difficulty can be resolved by excluding the very distant SNP pairs without losing map quality. Modern computational technology with parallel processing can be used to speed up the process of map construction. A composite likelihood approach employing LD maps for association mapping has successfully localised several causal variants. An application to Rheumatoid Arthritis (RA) is described here. This approach, utilising the genome-wide LD map, is very suitable for genome-wide association studies.
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Published date: 2008
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Local EPrints ID: 466437
URI: http://eprints.soton.ac.uk/id/eprint/466437
PURE UUID: 75aa4388-99e0-454d-abf7-d5a65b14bb05
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Date deposited: 05 Jul 2022 05:16
Last modified: 16 Mar 2024 20:42
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Author:
Tai-Yue Kuo
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