Provides scalable generalized linear and mixed effects models tailored for sequence count data analysis (e.g., analysis of 16S or RNA-seq data). Uses Dirichlet-multinomial sampling to quantify uncertainty in relative abundance or relative expression conditioned on observed count data.
Implements scale models as a generalization of normalizations which account for uncertainty in scale (e.g., total abundances) as described in Nixon et al. (2025) <doi:10.1186/s13059-025-03609-3> and McGovern et al. (2025) <doi:10.1101/2025.08.05.668734>.
| Version: |
1.0.0 |
| Depends: |
R (≥ 3.5) |
| Imports: |
purrr, lme4, lmerTest, parallel, MASS, nlme, abind, matrixStats, methods, stats |
| Suggests: |
rBeta2009, testthat (≥ 3.0.0), lmtest, sandwich, knitr, rmarkdown |
| Published: |
2026-01-31 |
| DOI: |
10.32614/CRAN.package.ALDEx3 (may not be active yet) |
| Author: |
Justin Silverman [aut, cre],
Greg Gloor [aut],
Kyle McGovern [aut, ctb] |
| Maintainer: |
Justin Silverman <JustinSilverman at psu.edu> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
ALDEx3 results |