Literature DB >> 10597515

Covariates in linkage analysis.

J P Rice1, N Rochberg, R J Neuman, N L Saccone, K Y Liu, X Zhang, R Culverhouse.   

Abstract

We apply a novel technique to detect significant covariates in linkage analysis using a logistic regression approach. An overall test of linkage is first performed to determine whether there is significant perturbation from the expected 50% sharing under the hypothesis of no linkage; if the overall test is significant, the importance of the individual covariate is assessed. In addition, association analyses were performed. These methods were applied to simulated data from multiple populations, and detected correct marker linkages and associations. No population heterogeneity was detected. These methods have the advantages of using all sib pairs and of providing a formal test for heterogeneity across populations.

Mesh:

Year:  1999        PMID: 10597515     DOI: 10.1002/gepi.13701707113

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


  5 in total

1.  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

2.  Linkage analysis using co-phenotypes in the BRIGHT study reveals novel potential susceptibility loci for hypertension.

Authors:  Chris Wallace; Ming-Zhan Xue; Stephen J Newhouse; Ana Carolina B Marcano; Abiodun K Onipinla; Beverley Burke; Johannie Gungadoo; Richard J Dobson; Morris Brown; John M Connell; Anna Dominiczak; G Mark Lathrop; John Webster; Martin Farrall; Charles Mein; Nilesh J Samani; Mark J Caulfield; David G Clayton; Patricia B Munroe
Journal:  Am J Hum Genet       Date:  2006-06-19       Impact factor: 11.025

3.  Incorporation of covariates in simultaneous localization of two linked loci using affected relative pairs.

Authors:  Yen-Feng Chiu; Jeng-Min Chiou; Kung-Yee Liang; Chun-Yi Lee
Journal:  BMC Genet       Date:  2010-07-14       Impact factor: 2.797

4.  The Familial Intracranial Aneurysm (FIA) study protocol.

Authors:  Joseph P Broderick; Laura R Sauerbeck; Tatiana Foroud; John Huston; Nathan Pankratz; Irene Meissner; Robert D Brown
Journal:  BMC Med Genet       Date:  2005-04-26       Impact factor: 2.103

5.  Genome wide significant linkage in schizophrenia conditioning on occurrence of depressive episodes.

Authors:  M L Hamshere; N M Williams; N Norton; H Williams; A G Cardno; S Zammit; L A Jones; K C Murphy; R D Sanders; G McCarthy; M Y Gray; G Jones; P Holmans; M C O'Donovan; M J Owen; N Craddock
Journal:  J Med Genet       Date:  2005-10-14       Impact factor: 6.318

  5 in total

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