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Accounting for relatedness in family-based association studies: application to Genetic Analysis Workshop 18 data
In the last few years, a bewildering variety of methods/software packages that use linear mixed models to account for sample relatedness on the basis of genome-wide genomic information have been proposed. We compared these approaches as implemented in the programs EMMAX, FaST-LMM, Gemma, and GenABEL...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143672/ https://www.ncbi.nlm.nih.gov/pubmed/25519407 http://dx.doi.org/10.1186/1753-6561-8-S1-S79 |
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author | Eu-ahsunthornwattana, Jakris Howey, Richard AJ Cordell, Heather J |
author_facet | Eu-ahsunthornwattana, Jakris Howey, Richard AJ Cordell, Heather J |
author_sort | Eu-ahsunthornwattana, Jakris |
collection | PubMed |
description | In the last few years, a bewildering variety of methods/software packages that use linear mixed models to account for sample relatedness on the basis of genome-wide genomic information have been proposed. We compared these approaches as implemented in the programs EMMAX, FaST-LMM, Gemma, and GenABEL (FASTA/GRAMMAR-Gamma) on the Genetic Analysis Workshop 18 data. All methods performed quite similarly and were successful in reducing the genomic control inflation factor to reasonable levels, particularly when the mean values of the observations were used, although more variation was observed when data from each time point were used individually. From a practical point of view, we conclude that it makes little difference to the results which method/software package is used, and the user can make the choice of package on the basis of personal taste or computational speed/convenience. |
format | Online Article Text |
id | pubmed-4143672 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41436722014-09-02 Accounting for relatedness in family-based association studies: application to Genetic Analysis Workshop 18 data Eu-ahsunthornwattana, Jakris Howey, Richard AJ Cordell, Heather J BMC Proc Proceedings In the last few years, a bewildering variety of methods/software packages that use linear mixed models to account for sample relatedness on the basis of genome-wide genomic information have been proposed. We compared these approaches as implemented in the programs EMMAX, FaST-LMM, Gemma, and GenABEL (FASTA/GRAMMAR-Gamma) on the Genetic Analysis Workshop 18 data. All methods performed quite similarly and were successful in reducing the genomic control inflation factor to reasonable levels, particularly when the mean values of the observations were used, although more variation was observed when data from each time point were used individually. From a practical point of view, we conclude that it makes little difference to the results which method/software package is used, and the user can make the choice of package on the basis of personal taste or computational speed/convenience. BioMed Central 2014-06-17 /pmc/articles/PMC4143672/ /pubmed/25519407 http://dx.doi.org/10.1186/1753-6561-8-S1-S79 Text en Copyright © 2014 Eu-ahsunthornwattana 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 Eu-ahsunthornwattana, Jakris Howey, Richard AJ Cordell, Heather J Accounting for relatedness in family-based association studies: application to Genetic Analysis Workshop 18 data |
title | Accounting for relatedness in family-based association studies: application to Genetic Analysis Workshop 18 data |
title_full | Accounting for relatedness in family-based association studies: application to Genetic Analysis Workshop 18 data |
title_fullStr | Accounting for relatedness in family-based association studies: application to Genetic Analysis Workshop 18 data |
title_full_unstemmed | Accounting for relatedness in family-based association studies: application to Genetic Analysis Workshop 18 data |
title_short | Accounting for relatedness in family-based association studies: application to Genetic Analysis Workshop 18 data |
title_sort | accounting for relatedness in family-based association studies: application to genetic analysis workshop 18 data |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143672/ https://www.ncbi.nlm.nih.gov/pubmed/25519407 http://dx.doi.org/10.1186/1753-6561-8-S1-S79 |
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