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powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis
SUMMARY: Genome-wide association studies (GWAS) have revealed thousands of genetic loci for common diseases. One of the main challenges in the post-GWAS era is to understand the causality of the genetic variants. Expression quantitative trait locus (eQTL) analysis is an effective way to address this...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9492284/ https://www.ncbi.nlm.nih.gov/pubmed/34009297 http://dx.doi.org/10.1093/bioinformatics/btab385 |
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author | Dong, Xianjun Li, Xiaoqi Chang, Tzuu-Wang Scherzer, Clemens R Weiss, Scott T Qiu, Weiliang |
author_facet | Dong, Xianjun Li, Xiaoqi Chang, Tzuu-Wang Scherzer, Clemens R Weiss, Scott T Qiu, Weiliang |
author_sort | Dong, Xianjun |
collection | PubMed |
description | SUMMARY: Genome-wide association studies (GWAS) have revealed thousands of genetic loci for common diseases. One of the main challenges in the post-GWAS era is to understand the causality of the genetic variants. Expression quantitative trait locus (eQTL) analysis is an effective way to address this question by examining the relationship between gene expression and genetic variation in a sufficiently powered cohort. However, it is frequently a challenge to determine the sample size at which a variant with a specific allele frequency will be detected to associate with gene expression with sufficient power. This is a particularly difficult task for single-cell RNAseq studies. Therefore, a user-friendly tool to estimate statistical power for eQTL analyses in both bulk tissue and single-cell data is needed. Here, we presented an R package called powerEQTL with flexible functions to estimate power, minimal sample size or detectable minor allele frequency for both bulk tissue and single-cell eQTL analysis. A user-friendly, program-free web application is also provided, allowing users to calculate and visualize the parameters interactively. AVAILABILITY AND IMPLEMENTATION: The powerEQTL R package source code and online tutorial are freely available at CRAN: https://cran.r-project.org/web/packages/powerEQTL/. The R shiny application is publicly hosted at https://bwhbioinfo.shinyapps.io/powerEQTL/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9492284 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-94922842022-09-22 powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis Dong, Xianjun Li, Xiaoqi Chang, Tzuu-Wang Scherzer, Clemens R Weiss, Scott T Qiu, Weiliang Bioinformatics Applications Notes SUMMARY: Genome-wide association studies (GWAS) have revealed thousands of genetic loci for common diseases. One of the main challenges in the post-GWAS era is to understand the causality of the genetic variants. Expression quantitative trait locus (eQTL) analysis is an effective way to address this question by examining the relationship between gene expression and genetic variation in a sufficiently powered cohort. However, it is frequently a challenge to determine the sample size at which a variant with a specific allele frequency will be detected to associate with gene expression with sufficient power. This is a particularly difficult task for single-cell RNAseq studies. Therefore, a user-friendly tool to estimate statistical power for eQTL analyses in both bulk tissue and single-cell data is needed. Here, we presented an R package called powerEQTL with flexible functions to estimate power, minimal sample size or detectable minor allele frequency for both bulk tissue and single-cell eQTL analysis. A user-friendly, program-free web application is also provided, allowing users to calculate and visualize the parameters interactively. AVAILABILITY AND IMPLEMENTATION: The powerEQTL R package source code and online tutorial are freely available at CRAN: https://cran.r-project.org/web/packages/powerEQTL/. The R shiny application is publicly hosted at https://bwhbioinfo.shinyapps.io/powerEQTL/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-05-19 /pmc/articles/PMC9492284/ /pubmed/34009297 http://dx.doi.org/10.1093/bioinformatics/btab385 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (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 | Applications Notes Dong, Xianjun Li, Xiaoqi Chang, Tzuu-Wang Scherzer, Clemens R Weiss, Scott T Qiu, Weiliang powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis |
title | powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis |
title_full | powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis |
title_fullStr | powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis |
title_full_unstemmed | powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis |
title_short | powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis |
title_sort | powereqtl: an r package and shiny application for sample size and power calculation of bulk tissue and single-cell eqtl analysis |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9492284/ https://www.ncbi.nlm.nih.gov/pubmed/34009297 http://dx.doi.org/10.1093/bioinformatics/btab385 |
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