Literature DB >> 16216012

Genome scans with gene-covariate interaction.

Jie Peng1, Hsiu-Khuern Tang, David Siegmund.   

Abstract

Genetic models for gene-covariate interactions are described. Methods of linkage analysis that utilize special features of these models and the corresponding score statistics are derived. Their power is compared with that of simple genome scans that ignore these special features, and substantial gains in power are observed when the gene-covariate interaction is strong. Quantitative trait mapping in randomly ascertained sibships and affected sibpair mapping are discussed. For the latter case, a simpler statistic is proposed that has similar performance to the score statistic, but does not require the estimation of nuisance parameters. Since the nuisance parameters are not estimable solely from affected sib-pair data, this statistic would be much easier to apply in practice. Similarities with linkage analysis of models for longitudinal data and multivariate phenotypes are also briefly discussed. Approximations for the P-value and power are derived under the framework of local alternatives. Copyright 2005 Wiley-Liss, Inc.

Mesh:

Year:  2005        PMID: 16216012     DOI: 10.1002/gepi.20100

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


  3 in total

1.  Powerful multilocus tests of genetic association in the presence of gene-gene and gene-environment interactions.

Authors:  Nilanjan Chatterjee; Zeynep Kalaylioglu; Roxana Moslehi; Ulrike Peters; Sholom Wacholder
Journal:  Am J Hum Genet       Date:  2006-10-20       Impact factor: 11.025

2.  Testing genetic linkage with relative pairs and covariates by quasi-likelihood score statistics.

Authors:  Daniel J Schaid; Jason P Sinnwell; Stephen N Thibodeau
Journal:  Hum Hered       Date:  2007-06-12       Impact factor: 0.444

3.  Mapping quantitative traits in unselected families: algorithms and examples.

Authors:  Josée Dupuis; Jianxin Shi; Alisa K Manning; Emelia J Benjamin; James B Meigs; L Adrienne Cupples; David Siegmund
Journal:  Genet Epidemiol       Date:  2009-11       Impact factor: 2.135

  3 in total

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