Comparison of Linkage and Association Strategies for Quantitative Traits Using the COGA Dataset

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Comparison of Linkage and Association Strategies for Quantitative Traits Using the COGA Dataset

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Title: Comparison of Linkage and Association Strategies for Quantitative Traits Using the COGA Dataset
Author: McQueen, Matthew B; Murphy, Amy; Kraft, Peter; Van Steen, Kristel; Su, Jessica Ann Lasky; Lazarus, Ross; Laird, Nan M.; Lange, Christoph

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Citation: McQueen, Matthew B., Amy Murphy, Peter Kraft, Jessica Su, Ross Lazarus, Nan M. Laird, Christoph Lange, and Kristel Van Steen. 2005. Comparison of linkage and association strategies for quantitative traits using the COGA dataset. BMC Genetics 6(Suppl 1): S96.
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Abstract: Genome scans using dense single-nucleotide polymorphism (SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the denser scans will help refine previously identified linkage regions and possibly identify new regions not identifiable using the sparser, microsatellite scans. In the context of the dense SNP scans, it is also possible to consider association strategies to provide even more information about potential regions of interest. To circumvent the multiple-testing issues inherent in association analysis, we use a recently developed strategy, implemented in PBAT, which screens the data to identify the optimal SNPs for testing, without biasing the nominal significance level. We compare the results from the PBAT analysis to that of quantitative linkage analysis on chromosome 4 using the Collaborative Study on the Genetics of Alcoholism data, as released through Genetic Analysis Workshop 14.
Published Version: doi:10.1186/1471-2156-6-S1-S96
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866683/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:8000901

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