EpipwR
This is the released version of EpipwR; for the devel version, see EpipwR.
Efficient Power Analysis for EWAS with Continuous or Binary Outcomes
Bioconductor version: Release (3.23)
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.
Author: Jackson Barth [aut, cre] 
, Austin Reynolds [aut], Mary Lauren Benton [ctb], Carissa Fong [ctb]
Maintainer: Jackson Barth <Jackson_Barth at Baylor.edu>
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.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("EpipwR")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("EpipwR")| EpipwR | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Epigenetics, ExperimentalDesign, Software |
| Version | 1.6.0 |
| In Bioconductor since | BioC 3.20 (R-4.4) (2 years) |
| License | Artistic-2.0 |
| Depends | R (>= 4.4.0) |
| Imports | EpipwR.data, ExperimentHub (>= 2.10.0), ggplot2 |
| System Requirements | |
| URL | https://github.com/jbarth216/EpipwR |
| Bug Reports | https://github.com/jbarth216/EpipwR |
See More
| Suggests | knitr, rmarkdown, testthat (>= 3.0.0), sessioninfo |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow 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 (64-bit only) |
| macOS Binary (big-sur-x86_64) | EpipwR_1.6.0.tgz |
| macOS Binary (sonoma-arm64) | EpipwR_1.6.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/EpipwR |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/EpipwR |
| Package Short Url | https://bioconductor.org/packages/EpipwR/ |
| Package Downloads Report | Download Stats |