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Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests
Advances in next-generation sequencing technology have enabled systematic exploration of the contribution of rare variation to Mendelian and complex diseases. Although it is well known that population stratification can generate spurious associations with common alleles, its impact on rare variant a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3701690/ https://www.ncbi.nlm.nih.gov/pubmed/23861739 http://dx.doi.org/10.1371/journal.pone.0065834 |
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author | O’Connor, Timothy D. Kiezun, Adam Bamshad, Michael Rich, Stephen S. Smith, Joshua D. Turner, Emily Leal, Suzanne M. Akey, Joshua M. |
author_facet | O’Connor, Timothy D. Kiezun, Adam Bamshad, Michael Rich, Stephen S. Smith, Joshua D. Turner, Emily Leal, Suzanne M. Akey, Joshua M. |
author_sort | O’Connor, Timothy D. |
collection | PubMed |
description | Advances in next-generation sequencing technology have enabled systematic exploration of the contribution of rare variation to Mendelian and complex diseases. Although it is well known that population stratification can generate spurious associations with common alleles, its impact on rare variant association methods remains poorly understood. Here, we performed exhaustive coalescent simulations with demographic parameters calibrated from exome sequence data to evaluate the performance of nine rare variant association methods in the presence of fine-scale population structure. We find that all methods have an inflated spurious association rate for parameter values that are consistent with levels of differentiation typical of European populations. For example, at a nominal significance level of 5%, some test statistics have a spurious association rate as high as 40%. Finally, we empirically assess the impact of population stratification in a large data set of 4,298 European American exomes. Our results have important implications for the design, analysis, and interpretation of rare variant genome-wide association studies. |
format | Online Article Text |
id | pubmed-3701690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37016902013-07-16 Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests O’Connor, Timothy D. Kiezun, Adam Bamshad, Michael Rich, Stephen S. Smith, Joshua D. Turner, Emily Leal, Suzanne M. Akey, Joshua M. PLoS One Research Article Advances in next-generation sequencing technology have enabled systematic exploration of the contribution of rare variation to Mendelian and complex diseases. Although it is well known that population stratification can generate spurious associations with common alleles, its impact on rare variant association methods remains poorly understood. Here, we performed exhaustive coalescent simulations with demographic parameters calibrated from exome sequence data to evaluate the performance of nine rare variant association methods in the presence of fine-scale population structure. We find that all methods have an inflated spurious association rate for parameter values that are consistent with levels of differentiation typical of European populations. For example, at a nominal significance level of 5%, some test statistics have a spurious association rate as high as 40%. Finally, we empirically assess the impact of population stratification in a large data set of 4,298 European American exomes. Our results have important implications for the design, analysis, and interpretation of rare variant genome-wide association studies. Public Library of Science 2013-07-04 /pmc/articles/PMC3701690/ /pubmed/23861739 http://dx.doi.org/10.1371/journal.pone.0065834 Text en © 2013 O'Connor et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article O’Connor, Timothy D. Kiezun, Adam Bamshad, Michael Rich, Stephen S. Smith, Joshua D. Turner, Emily Leal, Suzanne M. Akey, Joshua M. Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests |
title | Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests |
title_full | Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests |
title_fullStr | Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests |
title_full_unstemmed | Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests |
title_short | Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests |
title_sort | fine-scale patterns of population stratification confound rare variant association tests |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3701690/ https://www.ncbi.nlm.nih.gov/pubmed/23861739 http://dx.doi.org/10.1371/journal.pone.0065834 |
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