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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...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2003
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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. |
format | Text |
id | pubmed-1866488 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2003 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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