Literature DB >> 10782014

Adjusting for confounding due to population admixture when estimating the effect of candidate genes on quantitative traits.

Q Yang1, D Rabinowitz, C Isasi, S Shea.   

Abstract

When analyzing the relationship between allelic variability and traits, a potential source of confounding is population admixture. An approach to adjusting for potential confounding due to population admixture when estimating the influence of allelic variability at a candidate gene is presented. The approach involves augmenting linear regression models with additional regressors. Family genotype data are used to define the regressors, and inclusion of the regressors ensures that, even in the presence of population admixture, the estimates of the regression coefficients that parameterize the influence of allelic variability on the trait are unbiased. The approach is illustrated through an analysis of the influence of apolipoprotein E genotype on plasma low density lipoprotein cholesterol concentrations. Copyright 2000 S. Karger AG, Basel

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Year:  2000        PMID: 10782014     DOI: 10.1159/000022920

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  7 in total

1.  Unbiased and locally efficient estimation of genetic effect on quantitative trait in the presence of population admixture.

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2.  Candidate-gene association analysis for a continuous phenotype with a spike at zero using parent-offspring trios.

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Authors:  Ian J Welsby; Mihai V Podgoreanu; Barbara Phillips-Bute; Richard Morris; Joseph P Mathew; Peter K Smith; Mark F Newman; Debra A Schwinn; Mark Stafford-Smith
Journal:  J Cardiothorac Vasc Anesth       Date:  2010-01-06       Impact factor: 2.628

4.  Flexible semiparametric analysis of longitudinal genetic studies by reduced rank smoothing.

Authors:  Yuanjia Wang; Chiahui Huang; Yixin Fang; Qiong Yang; Runze Li
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2011-10-10       Impact factor: 1.864

5.  Gene-environment interaction testing in family-based association studies with phenotypically ascertained samples: a causal inference approach.

Authors:  David W Fardo; Jinze Liu; Dawn L Demeo; Edwin K Silverman; Stijn Vansteelandt
Journal:  Biostatistics       Date:  2011-11-13       Impact factor: 5.279

6.  Quantitative trait association in parent offspring trios: Extension of case/pseudocontrol method and comparison of prospective and retrospective approaches.

Authors:  Eleanor Wheeler; Heather J Cordell
Journal:  Genet Epidemiol       Date:  2007-12       Impact factor: 2.135

7.  Dosage transmission disequilibrium test (dTDT) for linkage and association detection.

Authors:  Zhehao Zhang; Jen-Chyong Wang; William Howells; Peng Lin; Arpana Agrawal; Howard J Edenberg; Jay A Tischfield; Marc A Schuckit; Laura J Bierut; Alison Goate; John P Rice
Journal:  PLoS One       Date:  2013-05-14       Impact factor: 3.240

  7 in total

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