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Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling
This paper describes an analysis of systolic blood pressure (SBP) in the Genetic Analysis Workshop 13 (GAW13) simulated data. The main aim was to assess evidence for both general and specific genetic effects on the baseline blood pressure and on the rate of change (slope) of blood pressure with time...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2003
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866460/ https://www.ncbi.nlm.nih.gov/pubmed/14975093 http://dx.doi.org/10.1186/1471-2156-4-S1-S25 |
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author | Scurrah, Katrina J Tobin, Martin D Burton, Paul R |
author_facet | Scurrah, Katrina J Tobin, Martin D Burton, Paul R |
author_sort | Scurrah, Katrina J |
collection | PubMed |
description | This paper describes an analysis of systolic blood pressure (SBP) in the Genetic Analysis Workshop 13 (GAW13) simulated data. The main aim was to assess evidence for both general and specific genetic effects on the baseline blood pressure and on the rate of change (slope) of blood pressure with time. Generalized linear mixed models were fitted using Gibbs sampling in WinBUGS, and the additive polygenic random effects estimated using these models were then used as continuous phenotypes in a variance components linkage analysis. The first-stage analysis provided evidence for general genetic effects on both the baseline and slope of blood pressure, and the linkage analysis found evidence of several genes, again for both baseline and slope. |
format | Text |
id | pubmed-1866460 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2003 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18664602007-05-11 Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling Scurrah, Katrina J Tobin, Martin D Burton, Paul R BMC Genet Proceedings This paper describes an analysis of systolic blood pressure (SBP) in the Genetic Analysis Workshop 13 (GAW13) simulated data. The main aim was to assess evidence for both general and specific genetic effects on the baseline blood pressure and on the rate of change (slope) of blood pressure with time. Generalized linear mixed models were fitted using Gibbs sampling in WinBUGS, and the additive polygenic random effects estimated using these models were then used as continuous phenotypes in a variance components linkage analysis. The first-stage analysis provided evidence for general genetic effects on both the baseline and slope of blood pressure, and the linkage analysis found evidence of several genes, again for both baseline and slope. BioMed Central 2003-12-31 /pmc/articles/PMC1866460/ /pubmed/14975093 http://dx.doi.org/10.1186/1471-2156-4-S1-S25 Text en Copyright © 2003 Scurrah 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 Scurrah, Katrina J Tobin, Martin D Burton, Paul R Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling |
title | Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling |
title_full | Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling |
title_fullStr | Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling |
title_full_unstemmed | Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling |
title_short | Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling |
title_sort | longitudinal variance components models for systolic blood pressure, fitted using gibbs sampling |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866460/ https://www.ncbi.nlm.nih.gov/pubmed/14975093 http://dx.doi.org/10.1186/1471-2156-4-S1-S25 |
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