Literature DB >> 9433613

Joint segregation and linkage analysis of a quantitative trait compared to separate analyses.

W J Gauderman1, C L Faucett, J L Morrison, C L Carpenter.   

Abstract

Our goal was to determine the degree to which joint segregation and linkage analysis leads to increased efficiency for estimating the recombination fraction and to greater power for detecting linkage, compared to separate analyses. We concentrated on the quantitative phenotype Q2 and analyzed linkage with a tightly linked marker, a loosely linked marker, and eight unlinked markers, the latter chosen to evaluate false positive rates. We considered both nuclear-family and extended-pedigree data, using the 200 replicates of each provided to GAW participants. We found joint analysis to be consistently more efficient, with relative efficiencies for the tightly linked marker of 1.16 and 1.06 in extended pedigrees and nuclear families, respectively. These relative efficiencies translated into modest but consistent gains in power to detect linkage. Both methods appear to produce unbiased parameter estimates and similar false positive rates.

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Year:  1997        PMID: 9433613     DOI: 10.1002/(SICI)1098-2272(1997)14:6<993::AID-GEPI72>3.0.CO;2-F

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  2 in total

1.  Modeling lung cancer risk in case-control studies using a new dose metric of smoking.

Authors:  Sally W Thurston; Geoffrey Liu; David P Miller; David C Christiani
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2005-10       Impact factor: 4.254

2.  Effects of measured susceptibility genes on cancer risk in family studies.

Authors:  Chih-Chieh Wu; Louise C Strong; Sanjay Shete
Journal:  Hum Genet       Date:  2009-12-29       Impact factor: 4.132

  2 in total

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