Coxmos

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.

Last 30 days

This package has been downloaded 295 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 2,659 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 21, 2024 with 74 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.