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Revisiting the genome-wide significance threshold for common variant GWAS

Over the last decade, GWAS meta-analyses have used a strict P-value threshold of 5 × 10(−8) to classify associations as significant. Here, we use our current understanding of frequently studied traits including lipid levels, height, and BMI to revisit this genome-wide significance threshold. We comp...

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Autores principales: Chen, Zhongsheng, Boehnke, Michael, Wen, Xiaoquan, Mukherjee, Bhramar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022962/
https://www.ncbi.nlm.nih.gov/pubmed/33585870
http://dx.doi.org/10.1093/g3journal/jkaa056
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author Chen, Zhongsheng
Boehnke, Michael
Wen, Xiaoquan
Mukherjee, Bhramar
author_facet Chen, Zhongsheng
Boehnke, Michael
Wen, Xiaoquan
Mukherjee, Bhramar
author_sort Chen, Zhongsheng
collection PubMed
description Over the last decade, GWAS meta-analyses have used a strict P-value threshold of 5 × 10(−8) to classify associations as significant. Here, we use our current understanding of frequently studied traits including lipid levels, height, and BMI to revisit this genome-wide significance threshold. We compare the performance of studies using the P = 5 × 10(−8) threshold in terms of true and false positive rate to other multiple testing strategies: (1) less stringent P-value thresholds, (2) controlling the FDR with the Benjamini–Hochberg and Benjamini–Yekutieli procedure, and (3) controlling the Bayesian FDR with posterior probabilities. We applied these procedures to re-analyze results from the Global Lipids and GIANT GWAS meta-analysis consortia and supported them with extensive simulation that mimics the empirical data. We observe in simulated studies with sample sizes ∼20,000 and >120,000 that relaxing the P-value threshold to 5 × 10(−7) increased discovery at the cost of 18% and 8% of additional loci being false positive results, respectively. FDR and Bayesian FDR are well controlled for both sample sizes with a few exceptions that disappear under a less stringent definition of true positives and the two approaches yield similar results. Our work quantifies the value of using a relaxed P-value threshold in large studies to increase their true positive discovery but also show the excess false positive rates due to such actions in modest-sized studies. These results may guide investigators considering different thresholds in replication studies and downstream work such as gene-set enrichment or pathway analysis. Finally, we demonstrate the viability of FDR-controlling procedures in GWAS.
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spelling pubmed-80229622021-04-09 Revisiting the genome-wide significance threshold for common variant GWAS Chen, Zhongsheng Boehnke, Michael Wen, Xiaoquan Mukherjee, Bhramar G3 (Bethesda) Investigation Over the last decade, GWAS meta-analyses have used a strict P-value threshold of 5 × 10(−8) to classify associations as significant. Here, we use our current understanding of frequently studied traits including lipid levels, height, and BMI to revisit this genome-wide significance threshold. We compare the performance of studies using the P = 5 × 10(−8) threshold in terms of true and false positive rate to other multiple testing strategies: (1) less stringent P-value thresholds, (2) controlling the FDR with the Benjamini–Hochberg and Benjamini–Yekutieli procedure, and (3) controlling the Bayesian FDR with posterior probabilities. We applied these procedures to re-analyze results from the Global Lipids and GIANT GWAS meta-analysis consortia and supported them with extensive simulation that mimics the empirical data. We observe in simulated studies with sample sizes ∼20,000 and >120,000 that relaxing the P-value threshold to 5 × 10(−7) increased discovery at the cost of 18% and 8% of additional loci being false positive results, respectively. FDR and Bayesian FDR are well controlled for both sample sizes with a few exceptions that disappear under a less stringent definition of true positives and the two approaches yield similar results. Our work quantifies the value of using a relaxed P-value threshold in large studies to increase their true positive discovery but also show the excess false positive rates due to such actions in modest-sized studies. These results may guide investigators considering different thresholds in replication studies and downstream work such as gene-set enrichment or pathway analysis. Finally, we demonstrate the viability of FDR-controlling procedures in GWAS. Oxford University Press 2021-01-11 /pmc/articles/PMC8022962/ /pubmed/33585870 http://dx.doi.org/10.1093/g3journal/jkaa056 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Investigation
Chen, Zhongsheng
Boehnke, Michael
Wen, Xiaoquan
Mukherjee, Bhramar
Revisiting the genome-wide significance threshold for common variant GWAS
title Revisiting the genome-wide significance threshold for common variant GWAS
title_full Revisiting the genome-wide significance threshold for common variant GWAS
title_fullStr Revisiting the genome-wide significance threshold for common variant GWAS
title_full_unstemmed Revisiting the genome-wide significance threshold for common variant GWAS
title_short Revisiting the genome-wide significance threshold for common variant GWAS
title_sort revisiting the genome-wide significance threshold for common variant gwas
topic Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022962/
https://www.ncbi.nlm.nih.gov/pubmed/33585870
http://dx.doi.org/10.1093/g3journal/jkaa056
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