Literature DB >> 9433617

Power of variance component linkage analysis to detect epistasis.

B D Mitchell1, S Ghosh, J L Schneider, G Birznieks, J Blangero.   

Abstract

Variance component methods are now being used in linkage analysis to detect genes influencing complex diseases. These methods are easily extended to allow for simultaneous estimation of both the additive effects of multiple loci on phenotypic variation (conditional oligogenic analysis) and the additive interaction (epistatic) effects among loci. We performed linkage analyses on 200 of the simulated replicates in order to evaluate the power to detect the main effects of MG1 and MG2 on Q1 as well as their interaction effects. The power to detect the main effect of MG1 was moderately good, although the power to detect MG2 and the MG1 x MG2 interaction was poor.

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Year:  1997        PMID: 9433617     DOI: 10.1002/(SICI)1098-2272(1997)14:6<1017::AID-GEPI76>3.0.CO;2-L

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


  12 in total

1.  Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome.

Authors:  A H Kissebah; G E Sonnenberg; J Myklebust; M Goldstein; K Broman; R G James; J A Marks; G R Krakower; H J Jacob; J Weber; L Martin; J Blangero; A G Comuzzie
Journal:  Proc Natl Acad Sci U S A       Date:  2000-12-19       Impact factor: 11.205

2.  A family-based association test to detect gene-gene interactions in the presence of linkage.

Authors:  Lizzy De Lobel; Lutgarde Thijs; Tatiana Kouznetsova; Jan A Staessen; Kristel Van Steen
Journal:  Eur J Hum Genet       Date:  2012-03-14       Impact factor: 4.246

3.  Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution.

Authors:  S H Lee; J H J Van der Werf
Journal:  Genetics       Date:  2006-09-01       Impact factor: 4.562

4.  Fine mapping of multiple interacting quantitative trait loci using combined linkage disequilibrium and linkage information.

Authors:  Sang Hong Lee; J H Julius van der Werf
Journal:  J Zhejiang Univ Sci B       Date:  2007-11       Impact factor: 3.066

5.  An improved method for quantitative trait loci detection and identification of within-line segregation in F2 intercross designs.

Authors:  Lars Rönnegård; Francois Besnier; Orjan Carlborg
Journal:  Genetics       Date:  2008-04       Impact factor: 4.562

6.  A Variance-Component Framework for Pedigree Analysis of Continuous and Categorical Outcomes.

Authors:  Michael P Epstein; Jessica E Hunter; Emily G Allen; Stephanie L Sherman; Xihong Lin; Michael Boehnke
Journal:  Stat Biosci       Date:  2009-11

Review 7.  Variance component methods for analysis of complex phenotypes.

Authors:  Laura Almasy; John Blangero
Journal:  Cold Spring Harb Protoc       Date:  2010-05

Review 8.  Mapping quantitative trait loci in humans: achievements and limitations.

Authors:  Partha P Majumder; Saurabh Ghosh
Journal:  J Clin Invest       Date:  2005-06       Impact factor: 14.808

9.  Systems genetics of the nuclear factor-κB signal transduction network. I. Detection of several quantitative trait loci potentially relevant to aging.

Authors:  Vincent P Diego; Joanne E Curran; Jac Charlesworth; Juan M Peralta; V Saroja Voruganti; Shelley A Cole; Thomas D Dyer; Matthew P Johnson; Eric K Moses; Harald H H Göring; Jeff T Williams; Anthony G Comuzzie; Laura Almasy; John Blangero; Sarah Williams-Blangero
Journal:  Mech Ageing Dev       Date:  2011-12-01       Impact factor: 5.432

10.  Single QTL effects, epistasis, and pleiotropy account for two-thirds of the phenotypic F(2) variance of growth and obesity in DU6i x DBA/2 mice.

Authors:  G A Brockmann; J Kratzsch; C S Haley; U Renne; M Schwerin; S Karle
Journal:  Genome Res       Date:  2000-12       Impact factor: 9.043

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