Package: EpipwR 1.1.0

Jackson Barth

EpipwR: Efficient Power Analysis for EWAS with Continuous or Binary Outcomes

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.

Authors:Jackson Barth [aut, cre], Austin Reynolds [aut], Mary Lauren Benton [ctb], Carissa Fong [ctb]

EpipwR_1.1.0.tar.gz
EpipwR_1.1.0.zip(r-4.5)EpipwR_1.1.0.zip(r-4.4)
EpipwR_1.1.0.tgz(r-4.5-any)EpipwR_1.1.0.tgz(r-4.4-any)
EpipwR_1.1.0.tar.gz(r-4.5-noble)EpipwR_1.1.0.tar.gz(r-4.4-noble)
EpipwR_1.1.0.tgz(r-4.4-emscripten)
EpipwR.pdf |EpipwR.html✨
EpipwR/json (API)
NEWS

# Install 'EpipwR' in R:

install.packages('EpipwR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jbarth216/epipwr/issues

On BioConductor:EpipwR-1.1.0(bioc 3.21)EpipwR-1.0.0(bioc 3.20)

epigenetics experimentaldesign

4.40 score 3 scripts 118 downloads 3 exports 75 dependencies

Last updated 5 months agofrom:d393930e98. Checks:4 OK, 3 ERROR. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 29 2025
R-4.5-win	ERROR	Mar 29 2025
R-4.5-mac	OK	Mar 29 2025
R-4.5-linux	ERROR	Mar 29 2025
R-4.4-win	ERROR	Mar 29 2025
R-4.4-mac	OK	Mar 29 2025
R-4.4-linux	OK	Mar 29 2025