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Combining controls can improve power in two-stage association studies
BACKGROUND: High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates, researchers typically seek to replicate findings in a second experiment on independent cohorts before proc...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6171163/ https://www.ncbi.nlm.nih.gov/pubmed/30285617 http://dx.doi.org/10.1186/s12863-018-0675-y |
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author | Liley, James |
author_facet | Liley, James |
author_sort | Liley, James |
collection | PubMed |
description | BACKGROUND: High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates, researchers typically seek to replicate findings in a second experiment on independent cohorts before proceeding with further analyses. This can be an expensive procedure, particularly when control samples are difficult to recruit or ascertain; for example in inter-disease comparisons, or studies on degenerative diseases. RESULTS: This paper presents a method in which control (or case) samples from the discovery cohort are re-used in a replication study. The theoretical implications of this method are discussed and simulated genome-wide association study (GWAS) tests are used to compare performance against the standard approach in a range of circumstances. Using similar methods, a procedure is proposed for ‘partial replication’ using a new independent cohort consisting of only controls. This methods can be used to provide some validation of findings when a full replication procedure is not possible. The new method has differing sensitivity to confounding in study cohorts compared to the standard procedure, which must be considered in its application. Type-1 error rates in these scenarios are analytically and empirically derived, and an online tool for comparing power and error rates is provided. CONCLUSIONS: In several common study designs, a shared-control method allows a substantial improvement in power while retaining type-1 error rate control. Although careful consideration must be made of all necessary assumptions, this method can enable more efficient use of data in GWAS and other applications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12863-018-0675-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6171163 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61711632018-10-10 Combining controls can improve power in two-stage association studies Liley, James BMC Genet Methodology Article BACKGROUND: High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates, researchers typically seek to replicate findings in a second experiment on independent cohorts before proceeding with further analyses. This can be an expensive procedure, particularly when control samples are difficult to recruit or ascertain; for example in inter-disease comparisons, or studies on degenerative diseases. RESULTS: This paper presents a method in which control (or case) samples from the discovery cohort are re-used in a replication study. The theoretical implications of this method are discussed and simulated genome-wide association study (GWAS) tests are used to compare performance against the standard approach in a range of circumstances. Using similar methods, a procedure is proposed for ‘partial replication’ using a new independent cohort consisting of only controls. This methods can be used to provide some validation of findings when a full replication procedure is not possible. The new method has differing sensitivity to confounding in study cohorts compared to the standard procedure, which must be considered in its application. Type-1 error rates in these scenarios are analytically and empirically derived, and an online tool for comparing power and error rates is provided. CONCLUSIONS: In several common study designs, a shared-control method allows a substantial improvement in power while retaining type-1 error rate control. Although careful consideration must be made of all necessary assumptions, this method can enable more efficient use of data in GWAS and other applications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12863-018-0675-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-03 /pmc/articles/PMC6171163/ /pubmed/30285617 http://dx.doi.org/10.1186/s12863-018-0675-y Text en © The Author(s) 2018 Open Access This 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 | Methodology Article Liley, James Combining controls can improve power in two-stage association studies |
title | Combining controls can improve power in two-stage association studies |
title_full | Combining controls can improve power in two-stage association studies |
title_fullStr | Combining controls can improve power in two-stage association studies |
title_full_unstemmed | Combining controls can improve power in two-stage association studies |
title_short | Combining controls can improve power in two-stage association studies |
title_sort | combining controls can improve power in two-stage association studies |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6171163/ https://www.ncbi.nlm.nih.gov/pubmed/30285617 http://dx.doi.org/10.1186/s12863-018-0675-y |
work_keys_str_mv | AT lileyjames combiningcontrolscanimprovepowerintwostageassociationstudies |