QuasiSeq: Analyzing RNA Sequencing Count Tables Using Quasi-Likelihood
Identify differentially expressed genes in RNA-seq count data using quasi-Poisson or quasi-negative binomial models with 'QL', 'QLShrink' and 'QLSpline' methods described by Lund, Nettleton, McCarthy, and Smyth (2012) <doi:10.1515/1544-6115.1826>. Report bias-reduced estimates of log fold changes.
| Version: |
1.0-11-0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
edgeR, mgcv, pracma, utils, grDevices, graphics |
| Suggests: |
BB, nleqslv |
| Enhances: |
stats |
| Published: |
2022-08-15 |
| Author: |
Steve Lund [aut, cre],
Long Qu [aut, ctb],
Klirk Bhasavanich [aut],
Ian Marschner [aut] (The author of glm2::glm.fit2, which was modified
slightly leading to glm.fit3 in this package.),
R Core Team [aut] (The author of stats::glm.fit, which was modified
slightly leading to glm.fit3 in this package.) |
| Maintainer: |
Steve Lund <lundsp at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| CRAN checks: |
QuasiSeq results |
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