A novel pseudo-value regression approach for the differential co-expression network analysis in expression data, which can incorporate additional clinical variables in the model. This is a direct regression modeling for the differential network analysis, and it is therefore computationally amenable for the most users. The full methodological details can be found in Ahn S et al (2023) <doi:10.1186/s12859-022-05123-w>.
| Version: | 1.0.6 |
| Depends: | R (≥ 3.5.0) |
| Imports: | dplyr, parallel, robustbase, stats, minet |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2024-09-22 |
| DOI: | 10.32614/CRAN.package.PRANA |
| Author: | Seungjun Ahn |
| Maintainer: | Seungjun Ahn <seungjun.ahn at mountsinai.org> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Language: | en-US |
| CRAN checks: | PRANA results |
| Reference manual: | PRANA.html , PRANA.pdf |
| Vignettes: |
UserManualPRANA (source, R code) |
| Package source: | PRANA_1.0.6.tar.gz |
| Windows binaries: | r-devel: PRANA_1.0.6.zip, r-release: PRANA_1.0.6.zip, r-oldrel: PRANA_1.0.6.zip |
| macOS binaries: | r-release (arm64): PRANA_1.0.6.tgz, r-oldrel (arm64): PRANA_1.0.6.tgz, r-release (x86_64): PRANA_1.0.6.tgz, r-oldrel (x86_64): PRANA_1.0.6.tgz |
| Old sources: | PRANA archive |
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