Coxmos: Cox MultiBlock Survival

This software package provides Cox survival analysis for high-dimensional and multiblock datasets. It encompasses a suite of functions dedicated from the classical Cox regression to newest analysis, including Cox proportional hazards model, Stepwise Cox regression, and Elastic-Net Cox regression, Sparse Partial Least Squares Cox regression (sPLS-COX) incorporating three distinct strategies, and two Multiblock-PLS Cox regression (MB-sPLS-COX) methods. This tool is designed to adeptly handle high-dimensional data, and provides tools for cross-validation, plot generation, and additional resources for interpreting results. While references are available within the corresponding functions, key literature is mentioned below. Terry M Therneau (2024) <https://CRAN.R-project.org/package=survival>, Noah Simon et al. (2011) <doi:10.18637/jss.v039.i05>, Philippe Bastien et al. (2005) <doi:10.1016/j.csda.2004.02.005>, Philippe Bastien (2008) <doi:10.1016/j.chemolab.2007.09.009>, Philippe Bastien et al. (2014) <doi:10.1093/bioinformatics/btu660>, Kassu Mehari Beyene and Anouar El Ghouch (2020) <doi:10.1002/sim.8671>, Florian Rohart et al. (2017) <doi:10.1371/journal.pcbi.1005752>.

Version: 1.0.2
Depends: R (≥ 4.1.0)
Imports: caret, cowplot, furrr, future, ggrepel, ggplot2, ggpubr, glmnet, MASS, mixOmics, progress, purrr, Rdpack, scattermore, stats, survcomp, survival, survminer, svglite, tidyr, utils
Suggests: nsROC, smoothROCtime, survivalROC, risksetROC, ggforce, knitr, RColorConesa, rmarkdown
Published: 2024-03-25
Author: Pedro Salguero García ORCID iD [aut, cre, rev], Sonia Tarazona Campos [ths], Ana Conesa Cegarra [ths], Kassu Mehari Beyene [ctb], Luis Meira Machado [ctb], Marta Sestelo [ctb], Artur Araújo [ctb]
Maintainer: Pedro Salguero García <pedrosalguerog at gmail.com>
BugReports: https://github.com/BiostatOmics/Coxmos/issues
License: CC BY 4.0
URL: https://github.com/BiostatOmics/Coxmos
NeedsCompilation: yes
Materials: README
CRAN checks: Coxmos results

Documentation:

Reference manual: Coxmos.pdf
Vignettes: Step-by-step guide to the MO-Coxmos pipeline
Step-by-step guide to the Coxmos pipeline

Downloads:

Package source: Coxmos_1.0.2.tar.gz
Windows binaries: r-prerel: Coxmos_1.0.2.zip, r-release: Coxmos_1.0.2.zip, r-oldrel: Coxmos_1.0.2.zip
macOS binaries: r-prerel (arm64): Coxmos_1.0.2.tgz, r-release (arm64): Coxmos_1.0.2.tgz, r-oldrel (arm64): Coxmos_1.0.2.tgz, r-prerel (x86_64): Coxmos_1.0.2.tgz, r-release (x86_64): Coxmos_1.0.2.tgz
Old sources: Coxmos archive

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