Literature DB >> 15716907

Genome-wide association studies: theoretical and practical concerns.

William Y S Wang1, Bryan J Barratt, David G Clayton, John A Todd.   

Abstract

To fully understand the allelic variation that underlies common diseases, complete genome sequencing for many individuals with and without disease is required. This is still not technically feasible. However, recently it has become possible to carry out partial surveys of the genome by genotyping large numbers of common SNPs in genome-wide association studies. Here, we outline the main factors - including models of the allelic architecture of common diseases, sample size, map density and sample-collection biases - that need to be taken into account in order to optimize the cost efficiency of identifying genuine disease-susceptibility loci.

Mesh:

Year:  2005        PMID: 15716907     DOI: 10.1038/nrg1522

Source DB:  PubMed          Journal:  Nat Rev Genet        ISSN: 1471-0056            Impact factor:   53.242


  372 in total

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Journal:  Hum Mol Genet       Date:  2012-01-06       Impact factor: 6.150

3.  Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets.

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Journal:  J Lipid Res       Date:  2010-04-26       Impact factor: 5.922

6.  Possible association of the GSK3β gene with the anxiety symptoms of major depressive disorder and P300 waveform.

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Review 7.  "Higher order" addiction molecular genetics: convergent data from genome-wide association in humans and mice.

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Journal:  Hum Genet       Date:  2013-11-12       Impact factor: 4.132

9.  Testing gene-gene interactions in genome wide association studies.

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Review 10.  The emerging molecular architecture of schizophrenia, polygenic risk scores and the clinical implications for GxE research.

Authors:  Conrad Iyegbe; Desmond Campbell; Amy Butler; Olesya Ajnakina; Pak Sham
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2014-01-17       Impact factor: 4.328

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