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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 [cre, aut, trl], Somnath Datta [ctb, ths] |
Maintainer: | Seungjun Ahn <seungjun.ahn at mountsinai.org> |
License: | GPL-3 |
NeedsCompilation: | no |
Language: | en-US |
CRAN checks: | PRANA results |
Reference manual: | 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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.