Identification of low frequency and rare variants for hypertension using sparse-data methods

Availability of genomic sequence data provides opportunities to study the role of low-frequency and rare variants in the etiology of complex disease. In this study, we conduct association analyses of hypertension status in the cohort of 1943 unrelated Mexican Americans provided by Genetic Analysis W...

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Detalles Bibliográficos
Autores principales: Shin, Ji-Hyung, Yi, Ruiyang, Bull, Shelley B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133522/
https://www.ncbi.nlm.nih.gov/pubmed/27980667
http://dx.doi.org/10.1186/s12919-016-0061-6
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author Shin, Ji-Hyung
Yi, Ruiyang
Bull, Shelley B.
author_facet Shin, Ji-Hyung
Yi, Ruiyang
Bull, Shelley B.
author_sort Shin, Ji-Hyung
collection PubMed
description Availability of genomic sequence data provides opportunities to study the role of low-frequency and rare variants in the etiology of complex disease. In this study, we conduct association analyses of hypertension status in the cohort of 1943 unrelated Mexican Americans provided by Genetic Analysis Workshop 19, focusing on exonic variants in MAP4 on chromosome 3. Our primary interest is to compare the performance of standard and sparse-data approaches for single-variant tests and variant-collapsing tests for sets of rare and low-frequency variants. We analyze both the real and the simulated phenotypes.
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spelling pubmed-51335222016-12-15 Identification of low frequency and rare variants for hypertension using sparse-data methods Shin, Ji-Hyung Yi, Ruiyang Bull, Shelley B. BMC Proc Proceedings Availability of genomic sequence data provides opportunities to study the role of low-frequency and rare variants in the etiology of complex disease. In this study, we conduct association analyses of hypertension status in the cohort of 1943 unrelated Mexican Americans provided by Genetic Analysis Workshop 19, focusing on exonic variants in MAP4 on chromosome 3. Our primary interest is to compare the performance of standard and sparse-data approaches for single-variant tests and variant-collapsing tests for sets of rare and low-frequency variants. We analyze both the real and the simulated phenotypes. BioMed Central 2016-10-11 /pmc/articles/PMC5133522/ /pubmed/27980667 http://dx.doi.org/10.1186/s12919-016-0061-6 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
Shin, Ji-Hyung
Yi, Ruiyang
Bull, Shelley B.
Identification of low frequency and rare variants for hypertension using sparse-data methods
title Identification of low frequency and rare variants for hypertension using sparse-data methods
title_full Identification of low frequency and rare variants for hypertension using sparse-data methods
title_fullStr Identification of low frequency and rare variants for hypertension using sparse-data methods
title_full_unstemmed Identification of low frequency and rare variants for hypertension using sparse-data methods
title_short Identification of low frequency and rare variants for hypertension using sparse-data methods
title_sort identification of low frequency and rare variants for hypertension using sparse-data methods
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133522/
https://www.ncbi.nlm.nih.gov/pubmed/27980667
http://dx.doi.org/10.1186/s12919-016-0061-6
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AT yiruiyang identificationoflowfrequencyandrarevariantsforhypertensionusingsparsedatamethods
AT bullshelleyb identificationoflowfrequencyandrarevariantsforhypertensionusingsparsedatamethods

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