Literature DB >> 8314079

A comparison of univariate and multivariate tests for genetic linkage.

C I Amos1, A E Laing.   

Abstract

A variety of robust and model-dependent genetic linkage methods were applied to log transformed lipid levels from a large pedigree in which the LDL receptor defect has been shown to segregate by molecular biologic techniques. Application of the Haseman-Elston and a variance-components based test for linkage identified LDL and cholesterol as cosegregating with the marker C3, which is genetically linked to the LDL receptor defect. Consideration of lipid fractions as a multivariate response identified (0.723 x cholesterol) - (0.551 x triglycerides) as most strongly supporting evidence for linkage with C3. Subsequent segregation and linkage analyses provided support for an autosomal dominant major gene influencing either LDL or the function of cholesterol and triglycerides. Genetic linkage to LDL was only mildly supported, with a maximum lod score of 0.51 at a recombination fraction of theta = 0.33. Genetic linkage of the linear function to C3 was more strongly supported, with a maximum lod score of 1.69 at theta = 0.09. Bivariate analysis of clinical affection (with either type IIa or type IIb hyperlipidemia) and quantitative measures (LDL or the linear function) generally led to decreased lod scores, indicating, in this pedigree, loss of information when using clinical affection.

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Year:  1993        PMID: 8314079     DOI: 10.1002/gepi.1370100657

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


  23 in total

1.  Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. I. Likelihood formulation and simulation results.

Authors:  J T Williams; P Van Eerdewegh; L Almasy; J Blangero
Journal:  Am J Hum Genet       Date:  1999-10       Impact factor: 11.025

2.  Testing the robustness of the new Haseman-Elston quantitative-trait loci-mapping procedure.

Authors:  D B Allison; J R Fernández; M Heo; T M Beasley
Journal:  Am J Hum Genet       Date:  2000-05-11       Impact factor: 11.025

3.  Genomewide scans of complex human diseases: true linkage is hard to find.

Authors:  J Altmüller; L J Palmer; G Fischer; H Scherb; M Wjst
Journal:  Am J Hum Genet       Date:  2001-09-14       Impact factor: 11.025

Review 4.  Review and evaluation of methods correcting for population stratification with a focus on underlying statistical principles.

Authors:  Hemant K Tiwari; Jill Barnholtz-Sloan; Nathan Wineinger; Miguel A Padilla; Laura K Vaughan; David B Allison
Journal:  Hum Hered       Date:  2008-03-31       Impact factor: 0.444

5.  Bivariate association analysis in selected samples: application to a GWAS of two bone mineral density phenotypes in males with high or low BMD.

Authors:  Aude Saint-Pierre; Jean-Marc Kaufman; Agnes Ostertag; Martine Cohen-Solal; Anne Boland; Kaatje Toye; Diana Zelenika; Mark Lathrop; Marie-Christine de Vernejoul; Maria Martinez
Journal:  Eur J Hum Genet       Date:  2011-03-23       Impact factor: 4.246

6.  Transmission-disequilibrium tests for quantitative traits.

Authors:  D B Allison
Journal:  Am J Hum Genet       Date:  1997-03       Impact factor: 11.025

7.  Projection regression models for multivariate imaging phenotype.

Authors:  Ja-an Lin; Hongtu Zhu; Rebecca Knickmeyer; Martin Styner; John Gilmore; Joseph G Ibrahim
Journal:  Genet Epidemiol       Date:  2012-07-16       Impact factor: 2.135

8.  Genetics of microstructure of cerebral white matter using diffusion tensor imaging.

Authors:  P Kochunov; D C Glahn; J L Lancaster; A M Winkler; S Smith; P M Thompson; L Almasy; R Duggirala; P T Fox; J Blangero
Journal:  Neuroimage       Date:  2010-01-29       Impact factor: 6.556

9.  Univariate/multivariate genome-wide association scans using data from families and unrelated samples.

Authors:  Lei Zhang; Yu-Fang Pei; Jian Li; Christopher J Papasian; Hong-Wen Deng
Journal:  PLoS One       Date:  2009-08-04       Impact factor: 3.240

10.  Family-based bivariate association tests for quantitative traits.

Authors:  Lei Zhang; Aaron J Bonham; Jian Li; Yu-Fang Pei; Jie Chen; Christopher J Papasian; Hong-Wen Deng
Journal:  PLoS One       Date:  2009-12-02       Impact factor: 3.240

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