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A statistical method for adjusting covariates in linkage analysis with sib pairs

BACKGROUND: We propose a statistical method that includes the use of longitudinal regression models and estimation procedures for adjusting for covariate effects in applying the Haseman-Elston (HE) method for linkage analysis. Our methodology, which uses the covariate adjusted trait, contains three...

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Autores principales: Wu, Colin O, Zheng, Gang, Leifer, Eric, Follmann, Dean, Lin, Jing-Ping
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2003
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866488/
https://www.ncbi.nlm.nih.gov/pubmed/14975119
http://dx.doi.org/10.1186/1471-2156-4-S1-S51
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author Wu, Colin O
Zheng, Gang
Leifer, Eric
Follmann, Dean
Lin, Jing-Ping
author_facet Wu, Colin O
Zheng, Gang
Leifer, Eric
Follmann, Dean
Lin, Jing-Ping
author_sort Wu, Colin O
collection PubMed
description BACKGROUND: We propose a statistical method that includes the use of longitudinal regression models and estimation procedures for adjusting for covariate effects in applying the Haseman-Elston (HE) method for linkage analysis. Our methodology, which uses the covariate adjusted trait, contains three steps: a) modelling the covariate-adjusted population means of quantitative traits through regression; b) estimating the value of covariate-adjusted quantitative traits; and c) evaluating the linkage between the adjusted trait values and the markers based on alleles shared identically by descent. RESULTS: We applied our adjusted HE method and the standard HE method in S.A.G.E. to the sib-pair subset of the Framingham Heart Study distributed by Genetic Analysis Workshop 13 with systolic blood pressure as the quantitative trait. Both methods gave similar patterns for the LOD scores, and exhibited highest multipoint LOD scores near location 70 cM of chromosome 12. CONCLUSION: The adjusted HE method has two major advantages over the standard HE method used in S.A.G.E.: a) it has the capability to handle longitudinal data; b) it provides a more natural approach for adjusting the repeatedly measured covariates from each subject.
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spelling pubmed-18664882007-05-11 A statistical method for adjusting covariates in linkage analysis with sib pairs Wu, Colin O Zheng, Gang Leifer, Eric Follmann, Dean Lin, Jing-Ping BMC Genet Proceedings BACKGROUND: We propose a statistical method that includes the use of longitudinal regression models and estimation procedures for adjusting for covariate effects in applying the Haseman-Elston (HE) method for linkage analysis. Our methodology, which uses the covariate adjusted trait, contains three steps: a) modelling the covariate-adjusted population means of quantitative traits through regression; b) estimating the value of covariate-adjusted quantitative traits; and c) evaluating the linkage between the adjusted trait values and the markers based on alleles shared identically by descent. RESULTS: We applied our adjusted HE method and the standard HE method in S.A.G.E. to the sib-pair subset of the Framingham Heart Study distributed by Genetic Analysis Workshop 13 with systolic blood pressure as the quantitative trait. Both methods gave similar patterns for the LOD scores, and exhibited highest multipoint LOD scores near location 70 cM of chromosome 12. CONCLUSION: The adjusted HE method has two major advantages over the standard HE method used in S.A.G.E.: a) it has the capability to handle longitudinal data; b) it provides a more natural approach for adjusting the repeatedly measured covariates from each subject. BioMed Central 2003-12-31 /pmc/articles/PMC1866488/ /pubmed/14975119 http://dx.doi.org/10.1186/1471-2156-4-S1-S51 Text en Copyright © 2003 Wu 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
Wu, Colin O
Zheng, Gang
Leifer, Eric
Follmann, Dean
Lin, Jing-Ping
A statistical method for adjusting covariates in linkage analysis with sib pairs
title A statistical method for adjusting covariates in linkage analysis with sib pairs
title_full A statistical method for adjusting covariates in linkage analysis with sib pairs
title_fullStr A statistical method for adjusting covariates in linkage analysis with sib pairs
title_full_unstemmed A statistical method for adjusting covariates in linkage analysis with sib pairs
title_short A statistical method for adjusting covariates in linkage analysis with sib pairs
title_sort statistical method for adjusting covariates in linkage analysis with sib pairs
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866488/
https://www.ncbi.nlm.nih.gov/pubmed/14975119
http://dx.doi.org/10.1186/1471-2156-4-S1-S51
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