Literature DB >> 10597523

A generalized estimating equations approach to linkage analysis in sibships in relation to multiple markers and exposure factors.

D C Thomas1, D Qian, W J Gauderman, K Siegmund, J L Morrison.   

Abstract

We describe a multiple regression approach to nonparametric linkage analysis in sibships incorporating multiple genetic loci, environmental covariates, and interactions. The covariance in trait residuals between sib pairs is treated as the dependent variable, regressed upon identical-by-descent sharing probabilities and interaction effects, using generalized estimating equations to allow for the correlations among multiple sib pairs within a sibship. Individual covariates can also be introduced in the model for the trait means. An application to the GAW11 simulated data revealed linkage with each of the four simulated loci, as well as gene x environment interactions of E1 with loci C and D and gene x gene interactions among the cluster of loci A, B, and D.

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Year:  1999        PMID: 10597523     DOI: 10.1002/gepi.13701707121

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


  3 in total

1.  Gene-trait similarity regression for multimarker-based association analysis.

Authors:  Jung-Ying Tzeng; Daowen Zhang; Sheng-Mao Chang; Duncan C Thomas; Marie Davidian
Journal:  Biometrics       Date:  2009-02-04       Impact factor: 2.571

2.  Bayesian hierarchical modeling of means and covariances of gene expression data within families.

Authors:  Roger Pique-Regi; John Morrison; Duncan C Thomas
Journal:  BMC Proc       Date:  2007-12-18

3.  Design considerations in a sib-pair study of linkage for susceptibility loci in cancer.

Authors:  Richard A Kerber; Christopher I Amos; Beow Y Yeap; Dianne M Finkelstein; Duncan C Thomas
Journal:  BMC Med Genet       Date:  2008-07-10       Impact factor: 2.103

  3 in total

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