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Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes
It is essential to develop adequate statistical methods to fully utilize information from longitudinal family studies. We extend our previous multipoint linkage disequilibrium approach—simultaneously accounting for correlations between markers and repeat measurements within subjects, and the correla...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133529/ https://www.ncbi.nlm.nih.gov/pubmed/27980655 http://dx.doi.org/10.1186/s12919-016-0049-2 |
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author | Chiu, Yen-Feng Lee, Chun-Yi Hsu, Fang-Chi |
author_facet | Chiu, Yen-Feng Lee, Chun-Yi Hsu, Fang-Chi |
author_sort | Chiu, Yen-Feng |
collection | PubMed |
description | It is essential to develop adequate statistical methods to fully utilize information from longitudinal family studies. We extend our previous multipoint linkage disequilibrium approach—simultaneously accounting for correlations between markers and repeat measurements within subjects, and the correlations between subjects in families—to detect loci relevant to disease through gene-based analysis. Estimates of disease loci and their genetic effects along with their 95 % confidence intervals (or significance levels) are reported. Four different phenotypes—ever having hypertension at 4 visits, incidence of hypertension, hypertension status at baseline only, and hypertension status at 4 visits—are studied using the proposed approach. The efficiency of estimates of disease locus positions (inverse of standard error) improves when using the phenotypes from 4 visits rather than using baseline only. |
format | Online Article Text |
id | pubmed-5133529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-51335292016-12-15 Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes Chiu, Yen-Feng Lee, Chun-Yi Hsu, Fang-Chi BMC Proc Proceedings It is essential to develop adequate statistical methods to fully utilize information from longitudinal family studies. We extend our previous multipoint linkage disequilibrium approach—simultaneously accounting for correlations between markers and repeat measurements within subjects, and the correlations between subjects in families—to detect loci relevant to disease through gene-based analysis. Estimates of disease loci and their genetic effects along with their 95 % confidence intervals (or significance levels) are reported. Four different phenotypes—ever having hypertension at 4 visits, incidence of hypertension, hypertension status at baseline only, and hypertension status at 4 visits—are studied using the proposed approach. The efficiency of estimates of disease locus positions (inverse of standard error) improves when using the phenotypes from 4 visits rather than using baseline only. BioMed Central 2016-10-18 /pmc/articles/PMC5133529/ /pubmed/27980655 http://dx.doi.org/10.1186/s12919-016-0049-2 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Chiu, Yen-Feng Lee, Chun-Yi Hsu, Fang-Chi Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes |
title | Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes |
title_full | Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes |
title_fullStr | Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes |
title_full_unstemmed | Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes |
title_short | Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes |
title_sort | multipoint association mapping for longitudinal family data: an application to hypertension phenotypes |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133529/ https://www.ncbi.nlm.nih.gov/pubmed/27980655 http://dx.doi.org/10.1186/s12919-016-0049-2 |
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