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Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data
We apply a family-based extension of the sequence kernel association test (SKAT) to 93 trios extracted from the 20 pedigrees in the Genetic Analysis Workshop 18 simulated data. Each extracted trio includes a unique set of parents to ensure conditionally independent trios are sampled. We compare the...
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/PMC4143708/ https://www.ncbi.nlm.nih.gov/pubmed/25519316 http://dx.doi.org/10.1186/1753-6561-8-S1-S27 |
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author | Huang, Jing Chen, Yong Swartz, Michael D Ionita-Laza, Iuliana |
author_facet | Huang, Jing Chen, Yong Swartz, Michael D Ionita-Laza, Iuliana |
author_sort | Huang, Jing |
collection | PubMed |
description | We apply a family-based extension of the sequence kernel association test (SKAT) to 93 trios extracted from the 20 pedigrees in the Genetic Analysis Workshop 18 simulated data. Each extracted trio includes a unique set of parents to ensure conditionally independent trios are sampled. We compare the empirical type I error and power between the family-based SKAT and the burden test under varying percentages of causal single-nucleotide polymorphisms included in the analysis. Our investigation using simulated data suggests that, under the setting used for Genetic Analysis Workshop 18 data, both the family-based SKAT and the burden test have limited power, and that there is no substantial impact of percentage of signal on the power of either test. The low power is partially a result of the small sample size. However, we find that both the family-based SKAT and the burden test are more powerful when we use only rare variants, rather than common variants, to test the association. |
format | Online Article Text |
id | pubmed-4143708 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41437082014-09-02 Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data Huang, Jing Chen, Yong Swartz, Michael D Ionita-Laza, Iuliana BMC Proc Proceedings We apply a family-based extension of the sequence kernel association test (SKAT) to 93 trios extracted from the 20 pedigrees in the Genetic Analysis Workshop 18 simulated data. Each extracted trio includes a unique set of parents to ensure conditionally independent trios are sampled. We compare the empirical type I error and power between the family-based SKAT and the burden test under varying percentages of causal single-nucleotide polymorphisms included in the analysis. Our investigation using simulated data suggests that, under the setting used for Genetic Analysis Workshop 18 data, both the family-based SKAT and the burden test have limited power, and that there is no substantial impact of percentage of signal on the power of either test. The low power is partially a result of the small sample size. However, we find that both the family-based SKAT and the burden test are more powerful when we use only rare variants, rather than common variants, to test the association. BioMed Central 2014-06-17 /pmc/articles/PMC4143708/ /pubmed/25519316 http://dx.doi.org/10.1186/1753-6561-8-S1-S27 Text en Copyright © 2014 Huang 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 Huang, Jing Chen, Yong Swartz, Michael D Ionita-Laza, Iuliana Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data |
title | Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data |
title_full | Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data |
title_fullStr | Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data |
title_full_unstemmed | Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data |
title_short | Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data |
title_sort | comparing the power of family-based association tests for sequence data with applications in the gaw18 simulated data |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143708/ https://www.ncbi.nlm.nih.gov/pubmed/25519316 http://dx.doi.org/10.1186/1753-6561-8-S1-S27 |
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