Comparing strategies for evaluation of candidate genes in case-control studies using family data

The goal of this analysis is to compare different test strategies for genetic association in case-control studies using related individuals. The first test is the trend test that is corrected for related individuals on the basis of identity-by-descent information. The second approach is to use gener...

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Detalles Bibliográficos
Autores principales: Tian, Xin, Joo, Jungnam, Wu, Colin O, Lin, Jing-Ping
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367598/
https://www.ncbi.nlm.nih.gov/pubmed/18466529
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author Tian, Xin
Joo, Jungnam
Wu, Colin O
Lin, Jing-Ping
author_facet Tian, Xin
Joo, Jungnam
Wu, Colin O
Lin, Jing-Ping
author_sort Tian, Xin
collection PubMed
description The goal of this analysis is to compare different test strategies for genetic association in case-control studies using related individuals. The first test is the trend test that is corrected for related individuals on the basis of identity-by-descent information. The second approach is to use generalized estimating equations to adjust for the correlation between relatives, and the third is the multiple outputation method. We compare the power of these test strategies in a simulation study, and apply these methods to a candidate gene dataset of Genetic Analysis Workshop 15 from the North American Rheumatoid Arthritis Consortium.
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spelling pubmed-23675982008-05-06 Comparing strategies for evaluation of candidate genes in case-control studies using family data Tian, Xin Joo, Jungnam Wu, Colin O Lin, Jing-Ping BMC Proc Proceedings The goal of this analysis is to compare different test strategies for genetic association in case-control studies using related individuals. The first test is the trend test that is corrected for related individuals on the basis of identity-by-descent information. The second approach is to use generalized estimating equations to adjust for the correlation between relatives, and the third is the multiple outputation method. We compare the power of these test strategies in a simulation study, and apply these methods to a candidate gene dataset of Genetic Analysis Workshop 15 from the North American Rheumatoid Arthritis Consortium. BioMed Central 2007-12-18 /pmc/articles/PMC2367598/ /pubmed/18466529 Text en Copyright © 2007 Tian et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Tian, Xin
Joo, Jungnam
Wu, Colin O
Lin, Jing-Ping
Comparing strategies for evaluation of candidate genes in case-control studies using family data
title Comparing strategies for evaluation of candidate genes in case-control studies using family data
title_full Comparing strategies for evaluation of candidate genes in case-control studies using family data
title_fullStr Comparing strategies for evaluation of candidate genes in case-control studies using family data
title_full_unstemmed Comparing strategies for evaluation of candidate genes in case-control studies using family data
title_short Comparing strategies for evaluation of candidate genes in case-control studies using family data
title_sort comparing strategies for evaluation of candidate genes in case-control studies using family data
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367598/
https://www.ncbi.nlm.nih.gov/pubmed/18466529
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AT joojungnam comparingstrategiesforevaluationofcandidategenesincasecontrolstudiesusingfamilydata
AT wucolino comparingstrategiesforevaluationofcandidategenesincasecontrolstudiesusingfamilydata
AT linjingping comparingstrategiesforevaluationofcandidategenesincasecontrolstudiesusingfamilydata

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