Into the post-HapMap era
Into the post-HapMap era
The HapMap Project has shifted genetic epidemiology of complex inheritance away from linkage into association mapping of genes affecting disease and response to therapy. Starting with a physical map produced by the Human Genome Project and recent investigation of structural polymorphisms in HapMap samples, population-specific linkage disequilibrium (LD) maps that accurately reflect the fine structure of blocks and steps have been created for use in association mapping, and by interpolation to increase the resolution of linkage maps. All this evidence can be integrated by meta-analysis if expressed as an estimated location and its standard error, a property apparently unique to composite likelihood, recently freed from autocorrelation by permutation of affection status. Methods that do not estimate a standard error are easier to apply, but may be misleading if a causal marker has not been typed. The month of June 2007 saw advances in genome-wide association scans (GWAS) for several diseases. Many questions remain to be answered if genetic epidemiology is to continue the significant contribution to medicine that its definition promises and its history illustrates
chromosome mapping, trends, review, genes, therapy, human, meta-analysis, human genome project, linkage disequilibrium, epidemiology, multifactorial inheritance, forecasting, methods, disease, humans, genetics, genome, linkage (genetics), history
727-742
Morton, N.E.
c668e2be-074a-4a0a-a2ca-e8f51830ebb7
2008
Morton, N.E.
c668e2be-074a-4a0a-a2ca-e8f51830ebb7
Abstract
The HapMap Project has shifted genetic epidemiology of complex inheritance away from linkage into association mapping of genes affecting disease and response to therapy. Starting with a physical map produced by the Human Genome Project and recent investigation of structural polymorphisms in HapMap samples, population-specific linkage disequilibrium (LD) maps that accurately reflect the fine structure of blocks and steps have been created for use in association mapping, and by interpolation to increase the resolution of linkage maps. All this evidence can be integrated by meta-analysis if expressed as an estimated location and its standard error, a property apparently unique to composite likelihood, recently freed from autocorrelation by permutation of affection status. Methods that do not estimate a standard error are easier to apply, but may be misleading if a causal marker has not been typed. The month of June 2007 saw advances in genome-wide association scans (GWAS) for several diseases. Many questions remain to be answered if genetic epidemiology is to continue the significant contribution to medicine that its definition promises and its history illustrates
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Published date: 2008
Keywords:
chromosome mapping, trends, review, genes, therapy, human, meta-analysis, human genome project, linkage disequilibrium, epidemiology, multifactorial inheritance, forecasting, methods, disease, humans, genetics, genome, linkage (genetics), history
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Local EPrints ID: 60087
URI: http://eprints.soton.ac.uk/id/eprint/60087
ISSN: 0065-2660
PURE UUID: 2b32555c-3766-415d-ba07-993a9fa2b718
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Date deposited: 03 Sep 2008
Last modified: 15 Mar 2024 11:18
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Author:
N.E. Morton
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