Package: Coxmos 1.1.2
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>.
Authors:
Coxmos_1.1.2.tar.gz
Coxmos_1.1.2.zip(r-4.5)Coxmos_1.1.2.zip(r-4.4)Coxmos_1.1.2.zip(r-4.3)
Coxmos_1.1.2.tgz(r-4.5-x86_64)Coxmos_1.1.2.tgz(r-4.5-arm64)Coxmos_1.1.2.tgz(r-4.4-x86_64)Coxmos_1.1.2.tgz(r-4.4-arm64)Coxmos_1.1.2.tgz(r-4.3-x86_64)Coxmos_1.1.2.tgz(r-4.3-arm64)
Coxmos_1.1.2.tar.gz(r-4.5-noble)Coxmos_1.1.2.tar.gz(r-4.4-noble)
Coxmos_1.1.2.tgz(r-4.4-emscripten)Coxmos_1.1.2.tgz(r-4.3-emscripten)
Coxmos.pdf |Coxmos.html✨
Coxmos/json (API)
# Install 'Coxmos' in R: |
install.packages('Coxmos', repos = c('https://biostatomics.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/biostatomics/coxmos/issues
- X_multiomic - X_multiomic Data
- X_proteomic - X_proteomic Data
- Y_multiomic - Y_multiomic Data
- Y_proteomic - Y_proteomic Data
Last updated 1 days agofrom:1df0ecd7e8. Checks:12 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 05 2025 |
R-4.5-win-x86_64 | OK | Mar 05 2025 |
R-4.5-mac-x86_64 | OK | Mar 05 2025 |
R-4.5-mac-aarch64 | OK | Mar 05 2025 |
R-4.5-linux-x86_64 | OK | Mar 05 2025 |
R-4.4-win-x86_64 | OK | Mar 05 2025 |
R-4.4-mac-x86_64 | OK | Mar 05 2025 |
R-4.4-mac-aarch64 | OK | Mar 05 2025 |
R-4.4-linux-x86_64 | OK | Mar 05 2025 |
R-4.3-win-x86_64 | OK | Mar 05 2025 |
R-4.3-mac-x86_64 | OK | Mar 05 2025 |
R-4.3-mac-aarch64 | OK | Mar 05 2025 |
Exports:coxcox.predictioncoxENcoxSWcv.coxENcv.isb.splsdacoxcv.isb.splsdrcoxcv.isb.splsdrcox_penaltycv.isb.splsicoxcv.mb.splsdacoxcv.mb.splsdrcoxcv.sb.splsdacoxcv.sb.splsdrcoxcv.sb.splsdrcox_penaltycv.sb.splsicoxcv.splsdacoxcv.splsdrcoxcv.splsdrcox_penaltycv.splsicoxdeleteNearZeroCoefficientOfVariationdeleteNearZeroCoefficientOfVariation.mbdeleteZeroOrNearZeroVariancedeleteZeroOrNearZeroVariance.mbeval_Coxmos_model_per_variableeval_Coxmos_model_per_variable.listeval_Coxmos_modelsfactorToBinarygetAutoKMgetAutoKM.listgetCutoffAutoKMgetCutoffAutoKM.listgetDesign.MBgetEPVgetEPV.mbgetTestKMgetTestKM.listisb.splsdacoxisb.splsdrcoxisb.splsdrcox_penaltyisb.splsicoxloadingplot.Coxmosmb.splsdacoxmb.splsdrcoxplot_cox.eventplot_cox.event.listplot_divergent.biplotplot_evaluationplot_evaluation.listplot_eventsplot_forestplot_forest.listplot_multipleObservations.LPplot_multipleObservations.LP.listplot_observation.eventDensityplot_observation.eventHistogramplot_observation.pseudobetaplot_observation.pseudobeta.listplot_PLS_Coxmosplot_proportionalHazardplot_proportionalHazard.listplot_pseudobetaplot_pseudobeta.listplot_time.listsave_ggplotsave_ggplot_lstsb.splsdacoxsb.splsdrcoxsb.splsdrcox_penaltysb.splsicoxsplsdacoxsplsdrcoxsplsdrcox_penaltysplsicoxw.starplot.Coxmos
Dependencies:abindbackportsbase64encBHBiocParallelbootbootstrapbroombslibcachemcarcarDatacaretclasscliclockcodetoolscolorspacecommonmarkcorpcorcorrplotcowplotcpp11crayoncurldata.tableDerivdiagramdigestdoBydplyre1071ellipseevaluateexactRankTestsfansifarverfastmapfontawesomeforeachformatRFormulafsfurrrfutile.loggerfutile.optionsfuturefuture.applygenericsggplot2ggpubrggrepelggsciggsignifggtextglmnetglobalsgluegowergridExtragridtextgsignalgtablehardhathighrhmshtmltoolshtmlwidgetsigraphipredisobanditeratorsjpegjquerylibjsonliteKernSmoothkm.ciKMsurvknitrlabelinglambda.rlatticelavalifecyclelistenvlme4lubridatemagrittrmarkdownMASSMatrixMatrixModelsmatrixStatsmaxstatmemoisemgcvmicrobenchmarkmimeminqamixOmicsModelMetricsmodelrmunsellmvtnormnlmenloptrnnetnumDerivparallellypatchworkpbkrtestpillarpkgconfigplyrpngpolynompracmaprettyunitspROCprodlimprogressprogressrproxypurrrquantregR6rappdirsrARPACKrbibutilsRColorBrewerRcppRcppEigenRdpackrecipesreformulasreshape2rglrlangrmarkdownrmetarpartRSpectrarstatixsassscalesscattermoreshapesnowSparseMsparsevctrsSQUAREMstringistringrSuppDistssurvcompsurvivalsurvivalROCsurvminersurvMiscsvglitesystemfontstibbletidyrtidyselecttimechangetimeDatetinytextzdbutf8vctrsviridisLitewithrxfunxml2xtableyamlzoo
Step-by-step guide to the Coxmos pipeline
Rendered fromCoxmos-pipeline.Rmd
usingknitr::rmarkdown
on Mar 05 2025.Last update: 2025-03-05
Started: 2023-09-18
Step-by-step guide to the MO-Coxmos pipeline
Rendered fromCoxmos-MO-pipeline.Rmd
usingknitr::rmarkdown
on Mar 05 2025.Last update: 2025-03-05
Started: 2023-09-18