Please use this identifier to cite or link to this item: http://dl.umsu.ac.ir/handle/Hannan/32592
Title: Comparison of Linkage and Association Strategies for Quantitative Traits Using the COGA Dataset
Authors: McQueen, Matthew B;Murphy, Amy;Kraft, Peter;Van Steen, Kristel;Su, Jessica Ann Lasky;Lazarus, Ross;Laird, Nan M.;Lange, Christoph
Year: 2005
Publisher: BioMed Central
Description: 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.
URI: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866683/pdf/
http://nrs.harvard.edu/urn-3:HUL.InstRepos:8000901
Standard no: 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.
1471-2156
Appears in Collections:HSPH Scholarly Articles

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