EpipwR
Efficient Power Analysis for EWAS with Continuous or Binary Outcomes
Bioconductor version: 3.23 · Package version: 1.6.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
A quasi-simulation based approach to performing power analysis for EWAS (Epigenome-wide association studies) with continuous or binary outcomes. 'EpipwR' relies on empirical EWAS datasets to determine power at specific sample sizes while keeping computational cost low. EpipwR can be run with a variety of standard statistical tests, controlling for either a false discovery rate or a family-wise type I error rate.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("EpipwR")Details
| Maintainer | Jackson Barth <Jackson_Barth@Baylor.edu> |
| Author | Jackson Barth [aut, cre] (ORCID: <https://orcid.org/0009-0009-6307-9928>), Austin Reynolds [aut], Mary Lauren Benton [ctb], Carissa Fong [ctb] |
| License | Artistic-2.0 |
| URL | https://github.com/jbarth216/EpipwR |
| Bug Reports | https://github.com/jbarth216/EpipwR |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Epigenetics, ExperimentalDesign, Software |
| Package Short Url | https://bioconductor.org/packages/EpipwR/ |
Citation
From within R, enter citation("EpipwR"):
Jackson Barth, Austin Reynolds. EpipwR: Efficient Power Analysis for EWAS with Continuous or Binary Outcomes. doi:10.18129/B9.bioc.EpipwR, R package version 1.6.0, https://bioconductor.org/packages/EpipwR.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | EpipwR_1.6.0.tar.gz |
| Windows binary (x86_64) | EpipwR_1.6.0.zip |
| macOS binary (arm64) | EpipwR_1.6.0.tgz |
| macOS binary (x86_64) | EpipwR_1.6.0.tgz |
Dependencies
Depends: R (>= 4.4.0)
Imports: EpipwR.data, ExperimentHub (>= 2.10.0), ggplot2
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), sessioninfo