Literature DB >> 11037320

Variance component methods for detecting complex trait loci.

J Blangero1, J T Williams, L Almasy.   

Abstract

Variance component-based linkage analysis has become a major statistical tool for the localization and evaluation of quantitative trait loci influencing complex phenotypes. The variance component approach has many benefits--it can, for example, be used to analyze large pedigrees, and it is able to accommodate multiple loci simultaneously in a true oligogenic model. Important biological phenomena such as genotype-environment interaction and epistasis are also examined easily in a variance component framework. In this chapter, we review the basic statistical features of variance component linkage analysis, with an emphasis on its power and robustness to distributional violations.

Mesh:

Year:  2001        PMID: 11037320     DOI: 10.1016/s0065-2660(01)42021-9

Source DB:  PubMed          Journal:  Adv Genet        ISSN: 0065-2660            Impact factor:   1.944


  73 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.  Trimming, weighting, and grouping SNPs in human case-control association studies.

Authors:  J Hoh; A Wille; J Ott
Journal:  Genome Res       Date:  2001-12       Impact factor: 9.043

3.  Large upward bias in estimation of locus-specific effects from genomewide scans.

Authors:  H H Göring; J D Terwilliger; J Blangero
Journal:  Am J Hum Genet       Date:  2001-10-09       Impact factor: 11.025

4.  Evidence for a gene influencing serum bilirubin on chromosome 2q telomere: a genomewide scan in the Framingham study.

Authors:  Jing-Ping Lin; L Adrienne Cupples; Peter W F Wilson; Nancy Heard-Costa; Christopher J O'Donnell
Journal:  Am J Hum Genet       Date:  2003-02-28       Impact factor: 11.025

5.  Inherent bias toward the null hypothesis in conventional multipoint nonparametric linkage analysis.

Authors:  Nicholas J Schork; Tiffany A Greenwood
Journal:  Am J Hum Genet       Date:  2004-01-19       Impact factor: 11.025

6.  Genome-wide linkage analysis for ocular and nasal anthropometric traits in a Mongolian population.

Authors:  Sun-Wha Im; Hyun-Jin Kim; Mi Kyeong Lee; Jae-hyuk Yi; Ganchimeg Jargal; Joohon Sung; Sung-il Cho; Jong-Il Kim
Journal:  Exp Mol Med       Date:  2010-12-31       Impact factor: 8.718

7.  Clinical correlates and heritability of erythrocyte eicosapentaenoic and docosahexaenoic acid content in the Framingham Heart Study.

Authors:  William S Harris; James V Pottala; Sean M Lacey; Ramachandran S Vasan; Martin G Larson; Sander J Robins
Journal:  Atherosclerosis       Date:  2012-06-07       Impact factor: 5.162

8.  Bivariate genome-wide scan for metabolic phenotypes in non-diabetic Chinese individuals from the Stanford, Asia and Pacific Program of Hypertension and Insulin Resistance Family Study.

Authors:  Y-F Chiu; L-M Chuang; H-Y Kao; L-T Ho; C-T Ting; Y-J Hung; Y-D Chen; T Donlon; J D Curb; T Quertermous; C A Hsiung
Journal:  Diabetologia       Date:  2007-06-20       Impact factor: 10.122

9.  Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies.

Authors:  Anderson M Winkler; Peter Kochunov; John Blangero; Laura Almasy; Karl Zilles; Peter T Fox; Ravindranath Duggirala; David C Glahn
Journal:  Neuroimage       Date:  2009-12-16       Impact factor: 6.556

10.  Hypoplastic left heart syndrome links to chromosomes 10q and 6q and is genetically related to bicuspid aortic valve.

Authors:  Robert B Hinton; Lisa J Martin; Smitha Rame-Gowda; Meredith E Tabangin; Linda H Cripe; D Woodrow Benson
Journal:  J Am Coll Cardiol       Date:  2009-03-24       Impact factor: 24.094

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