Literature DB >> 11287739

Testing quantitative traits for association and linkage in the presence or absence of parental data.

X Zhu1, R C Elston, R S Cooper.   

Abstract

Zhu and Elston developed a transmission disequilibrium test for quantitative traits by defining a linear transformation to condition out founder information. The method tests the null hypothesis of no linkage or association and can be applied to general pedigree structures. However, this method requires both genotype and phenotype parental information, which may be difficult to obtain. In this paper, we describe parametric and non-parametric methods to relax this requirement when only nuclear families are sampled. We show that neither method is affected by population stratification in the absence of linkage. The statistical power and validity of the tests are investigated by simulation. A simple simulation method to calculate the power of the nonparametric method is also discussed. In practice, the data may have some families with parental phenotype and genotype information available and some without. We briefly discuss how all the data may be analyzed jointly. Copyright 2001 S. Karger AG, Basel.

Mesh:

Year:  2001        PMID: 11287739     DOI: 10.1159/000053341

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


  3 in total

1.  Power and design considerations for a general class of family-based association tests: quantitative traits.

Authors:  Christoph Lange; Dawn L DeMeo; Nan M Laird
Journal:  Am J Hum Genet       Date:  2002-11-21       Impact factor: 11.025

Review 2.  Linkage disequilibrium analysis of the renin-angiotensin system genes.

Authors:  Xiaofeng Zhu; Richard S Cooper
Journal:  Curr Hypertens Rep       Date:  2003-02       Impact factor: 5.369

3.  A unified association analysis approach for family and unrelated samples correcting for stratification.

Authors:  Xiaofeng Zhu; Shengchao Li; Richard S Cooper; Robert C Elston
Journal:  Am J Hum Genet       Date:  2008-02       Impact factor: 11.025

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.