Literature DB >> 12931047

Regression models for linkage: issues of traits, covariates, heterogeneity, and interaction.

Daniel J Schaid1, Jane M Olson, W James Gauderman, Robert C Elston.   

Abstract

Regression methods offer a common framework to analyze linkage for quantitative trait loci as well as linkage for affection status using affected sib-pairs. Although numerous papers on regression methods for linkage have been published, some common themes and important caveats tend to be scattered across the literature. For example, the typical approach is to regress a function of traits on identical-by-descent (IBD) information, but the reversal (regression of IBD on a function of traits) offers important insights. A second example is the use of regression equations to assess linkage heterogeneity or gene-environment interaction, and why these two different etiologies are difficult to distinguish with affected sib-pair data. A third example has to do with the differences, and similarities, between linear regression and non-linear regression methods for affected sib-pair data. The purposes of this paper are to review some recent developments in the linkage regression framework, to emphasize strengths and weaknesses of various proposed methods, and to highlight some important assumptions and caveats. Copyright 2003 S. Karger AG, Basel

Mesh:

Year:  2003        PMID: 12931047     DOI: 10.1159/000072313

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


  13 in total

1.  Mathematical assumptions versus biological reality: myths in affected sib pair linkage analysis.

Authors:  Robert C Elston; Danhong Song; Sudha K Iyengar
Journal:  Am J Hum Genet       Date:  2004-11-11       Impact factor: 11.025

2.  The affected-/discordant-sib-pair design can guarantee validity of multipoint model-free linkage analysis of incomplete pedigrees when there is marker-marker disequilibrium.

Authors:  Chao Xing; Ritwik Sinha; Guan Xing; Qing Lu; Robert C Elston
Journal:  Am J Hum Genet       Date:  2006-06-26       Impact factor: 11.025

3.  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

Review 4.  Gene--environment-wide association studies: emerging approaches.

Authors:  Duncan Thomas
Journal:  Nat Rev Genet       Date:  2010-04       Impact factor: 53.242

5.  Heritability Estimation using Regression Models for Correlation.

Authors:  Hye-Seung Lee; Myunghee Cho Paik; Tatjana Rundek; Ralph L Sacco; Chuanhui Dong; Jeffrey P Krischer
Journal:  J Biom Biostat       Date:  2011-11-15

6.  Genetic variation in HTR2A influences serotonin transporter binding potential as measured using PET and [11C]DASB.

Authors:  Gonzalo Laje; Dara M Cannon; Andrew S Allen; Jackie M Klaver; Summer A Peck; Xinmin Liu; Husseini K Manji; Wayne C Drevets; Francis J McMahon
Journal:  Int J Neuropsychopharmacol       Date:  2010-01-05       Impact factor: 5.176

7.  Using linkage analysis to identify quantitative trait loci for sleep apnea in relationship to body mass index.

Authors:  E K Larkin; S R Patel; R C Elston; C Gray-McGuire; X Zhu; S Redline
Journal:  Ann Hum Genet       Date:  2008-08-26       Impact factor: 1.670

8.  A genomic scan for age at onset of Alzheimer's disease in 437 families from the NIMH Genetic Initiative.

Authors:  M Ryan Dickson; Jian Li; Howard W Wiener; Rodney T Perry; Deborah Blacker; Susan S Bassett; Rodney C P Go
Journal:  Am J Med Genet B Neuropsychiatr Genet       Date:  2008-09-05       Impact factor: 3.568

9.  Uncoupling protein 2 gene polymorphisms are associated with obesity.

Authors:  Sukma Oktavianthi; Hidayat Trimarsanto; Clarissa A Febinia; Ketut Suastika; Made R Saraswati; Pande Dwipayana; Wibowo Arindrarto; Herawati Sudoyo; Safarina G Malik
Journal:  Cardiovasc Diabetol       Date:  2012-04-25       Impact factor: 9.951

10.  Linkage analysis of alcohol dependence using both affected and discordant sib pairs.

Authors:  Pei-Ying Shih; Tao Wang; Chao Xing; Moumita Sinha; Yeunjoo Song; Robert C Elston
Journal:  BMC Genet       Date:  2005-12-30       Impact factor: 2.797

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