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We provide new tools for the identification of prognostic and predictive biomarkers. For further details we refer the reader to the paper: Zhu et al. Identification of prognostic and predictive biomarkers in high-dimensional data with PPLasso. BMC Bioinformatics. 2023 Jan 23;24(1):25.
| Version: | 2.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | genlasso, ggplot2, cvCovEst, glmnet, MASS |
| Suggests: | knitr, rmarkdown |
| Published: | 2023-02-27 |
| Author: | Wencan Zhu [aut, cre], Celine Levy-Leduc [ctb], Nils Ternes [ctb] |
| Maintainer: | Wencan Zhu <wencan.zhu at agroparistech.fr> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | PPLasso results |
| Reference manual: | PPLasso.pdf |
| Vignettes: |
WLasso package |
| Package source: | PPLasso_2.0.tar.gz |
| Windows binaries: | r-devel: PPLasso_2.0.zip, r-release: PPLasso_2.0.zip, r-oldrel: PPLasso_2.0.zip |
| macOS binaries: | r-release (arm64): PPLasso_2.0.tgz, r-oldrel (arm64): PPLasso_2.0.tgz, r-release (x86_64): PPLasso_2.0.tgz, r-oldrel (x86_64): PPLasso_2.0.tgz |
| Old sources: | PPLasso archive |
Please use the canonical form https://CRAN.R-project.org/package=PPLasso to link to this page.
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.
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