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Association analysis of whole genome sequencing data accounting for longitudinal and family designs

Using the whole genome sequencing data and the simulated longitudinal phenotypes for 849 pedigree-based individuals from Genetic Analysis Workshop 18, we investigated various approaches to detecting the association of rare and common variants with blood pressure traits. We compared three strategies...

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Detalles Bibliográficos
Autores principales: Hu, Yijuan, Hui, Qin, Sun, Yan V
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143808/
https://www.ncbi.nlm.nih.gov/pubmed/25519416
http://dx.doi.org/10.1186/1753-6561-8-S1-S89
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author Hu, Yijuan
Hui, Qin
Sun, Yan V
author_facet Hu, Yijuan
Hui, Qin
Sun, Yan V
author_sort Hu, Yijuan
collection PubMed
description Using the whole genome sequencing data and the simulated longitudinal phenotypes for 849 pedigree-based individuals from Genetic Analysis Workshop 18, we investigated various approaches to detecting the association of rare and common variants with blood pressure traits. We compared three strategies for longitudinal data: (a) using the baseline measurement only, (b) using the average from multiple visits, and (c) using all individual measurements. We also compared the power of using all of the pedigree-based data and the unrelated subset. The analyses were performed without knowledge of the underlying simulating model.
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spelling pubmed-41438082014-09-02 Association analysis of whole genome sequencing data accounting for longitudinal and family designs Hu, Yijuan Hui, Qin Sun, Yan V BMC Proc Proceedings Using the whole genome sequencing data and the simulated longitudinal phenotypes for 849 pedigree-based individuals from Genetic Analysis Workshop 18, we investigated various approaches to detecting the association of rare and common variants with blood pressure traits. We compared three strategies for longitudinal data: (a) using the baseline measurement only, (b) using the average from multiple visits, and (c) using all individual measurements. We also compared the power of using all of the pedigree-based data and the unrelated subset. The analyses were performed without knowledge of the underlying simulating model. BioMed Central 2014-06-17 /pmc/articles/PMC4143808/ /pubmed/25519416 http://dx.doi.org/10.1186/1753-6561-8-S1-S89 Text en Copyright © 2014 Hu 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Proceedings
Hu, Yijuan
Hui, Qin
Sun, Yan V
Association analysis of whole genome sequencing data accounting for longitudinal and family designs
title Association analysis of whole genome sequencing data accounting for longitudinal and family designs
title_full Association analysis of whole genome sequencing data accounting for longitudinal and family designs
title_fullStr Association analysis of whole genome sequencing data accounting for longitudinal and family designs
title_full_unstemmed Association analysis of whole genome sequencing data accounting for longitudinal and family designs
title_short Association analysis of whole genome sequencing data accounting for longitudinal and family designs
title_sort association analysis of whole genome sequencing data accounting for longitudinal and family designs
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143808/
https://www.ncbi.nlm.nih.gov/pubmed/25519416
http://dx.doi.org/10.1186/1753-6561-8-S1-S89
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