depower: Power Analysis for Differential Expression Studies
Provides a convenient framework to simulate data, run hypothesis tests,
estimate power, and plot the results for differential expression studies. The
simulation-based framework is described in Klamer and Yu (2026)
<doi:10.1177/11769351261431247>. Outcomes may be lognormal, negative
binomial, or bivariate negative binomial. Supported designs are one-sample,
independent two-sample, and dependent two-sample comparisons. Built-in tests
include t-tests, Wald tests, and likelihood ratio tests. User-defined tests are
also accepted. The significance level can be set to control the per-family error
rate or the family-wise error rate. Negative binomial methods are described
in Yu, Fernandez, and Brock (2017) <doi:10.1186/s12859-017-1648-2>
and Yu, Fernandez, and Brock (2020) <doi:10.1186/s12859-020-3541-7>.
| Version: |
2026.11.11 |
| Depends: |
R (≥ 4.5.0) |
| Imports: |
Rdpack, stats, mvnfast, glmmTMB, dplyr, multidplyr, ggplot2, scales |
| Suggests: |
tinytest, rmarkdown |
| Published: |
2026-11-12 |
| DOI: |
10.32614/CRAN.package.depower |
| Author: |
Brett Klamer 
[aut, cre],
Lianbo Yu [aut] |
| Maintainer: |
Brett Klamer <code at brettklamer.com> |
| License: |
MIT + file LICENSE |
| URL: |
https://brettklamer.com/work/depower/,
https://bitbucket.org/bklamer/depower/ |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Citation: |
depower citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
depower results |
Documentation:
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