Longitudinal variance-components analysis of the Framingham Heart Study data

The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The...

Full description

Bibliographic Details
Main Authors:	Macgregor, Stuart, Knott, Sara A, White, Ian, Visscher, Peter M
Format:	Online
Language:	English
Published:	BioMed Central 2003
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866457/

id	pubmed-1866457
recordtype	oai_dc
spelling	pubmed-18664572007-05-11 Longitudinal variance-components analysis of the Framingham Heart Study data Macgregor, Stuart Knott, Sara A White, Ian Visscher, Peter M Proceedings The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records). BioMed Central 2003-12-31 /pmc/articles/PMC1866457/ /pubmed/14975090 http://dx.doi.org/10.1186/1471-2156-4-S1-S22 Text en Copyright © 2003 Macgregor 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.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Macgregor, Stuart Knott, Sara A White, Ian Visscher, Peter M
spellingShingle	Macgregor, Stuart Knott, Sara A White, Ian Visscher, Peter M Longitudinal variance-components analysis of the Framingham Heart Study data
author_facet	Macgregor, Stuart Knott, Sara A White, Ian Visscher, Peter M
author_sort	Macgregor, Stuart
title	Longitudinal variance-components analysis of the Framingham Heart Study data
title_short	Longitudinal variance-components analysis of the Framingham Heart Study data
title_full	Longitudinal variance-components analysis of the Framingham Heart Study data
title_fullStr	Longitudinal variance-components analysis of the Framingham Heart Study data
title_full_unstemmed	Longitudinal variance-components analysis of the Framingham Heart Study data
title_sort	longitudinal variance-components analysis of the framingham heart study data
description	The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records).
publisher	BioMed Central
publishDate	2003
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866457/
_version_	1611396201145434112

Longitudinal variance-components analysis of the Framingham Heart Study data

Similar Items