Package: ePCR 0.11.0

ePCR: Ensemble Penalized Cox Regression for Survival Prediction

The top-performing ensemble-based Penalized Cox Regression (ePCR) framework developed during the DREAM 9.5 mCRPC Prostate Cancer Challenge <https://www.synapse.org/ProstateCancerChallenge> presented in Guinney J, Wang T, Laajala TD, et al. (2017) <doi:10.1016/S1470-2045(16)30560-5> is provided here-in, together with the corresponding follow-up work. While initially aimed at modeling the most advanced stage of prostate cancer, metastatic Castration-Resistant Prostate Cancer (mCRPC), the modeling framework has subsequently been extended to cover also the non-metastatic form of advanced prostate cancer (CRPC). Readily fitted ensemble-based model S4-objects are provided, and a simulated example dataset based on a real-life cohort is provided from the Turku University Hospital, to illustrate the use of the package. Functionality of the ePCR methodology relies on constructing ensembles of strata in patient cohorts and averaging over them, with each ensemble member consisting of a highly optimized penalized/regularized Cox regression model. Various cross-validation and other modeling schema are provided for constructing novel model objects.

Authors:Teemu Daniel Laajala <[email protected]> [aut, cre], Mika Murtojarvi <[email protected]> [ctb]

ePCR_0.11.0.tar.gz
ePCR_0.11.0.zip(r-4.5)ePCR_0.11.0.zip(r-4.4)ePCR_0.11.0.zip(r-4.3)
ePCR_0.11.0.tgz(r-4.4-any)ePCR_0.11.0.tgz(r-4.3-any)
ePCR_0.11.0.tar.gz(r-4.5-noble)ePCR_0.11.0.tar.gz(r-4.4-noble)
ePCR_0.11.0.tgz(r-4.4-emscripten)ePCR_0.11.0.tgz(r-4.3-emscripten)
ePCR.pdf |ePCR.html✨
ePCR/json (API)
NEWS

# Install 'ePCR' in R:
install.packages('ePCR', repos = c('https://syksy.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/syksy/epcr/issues

Datasets:
  • DREAM - FIMM-UTU DREAM winning implementation of an ensemble of Penalized Cox Regression models for mCPRC research
  • TYKS - EPCR model fitted to the Turku University Hospital cohorts
  • TYKS_reduced - EPCR model fitted to the Turku University Hospital cohorts
  • xMEDISIMU - TYKSSIMU - simulated data matrices and survival responses from Turku University Hospital
  • xTEXTSIMU - TYKSSIMU - simulated data matrices and survival responses from Turku University Hospital
  • yMEDISIMU - TYKSSIMU - simulated data matrices and survival responses from Turku University Hospital
  • yTEXTSIMU - TYKSSIMU - simulated data matrices and survival responses from Turku University Hospital

On CRAN:

5.58 score 19 scripts 233 downloads 12 mentions 25 exports 110 dependencies

Last updated 9 months agofrom:629d3b96e0. Checks:OK: 5 WARNING: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-winOKNov 15 2024
R-4.5-linuxOKNov 15 2024
R-4.4-winOKNov 15 2024
R-4.4-macOKNov 15 2024
R-4.3-winWARNINGNov 15 2024
R-4.3-macWARNINGNov 15 2024

Exports:bootstrapRegCoefscoefconforminputcvcv.alphacv.gridheatcvintegrateRegCurveinteract.allinteract.partmeanrankNelsonAalennormriskrankplotpredictprintPSP.BOXPSP.CSPPSP.KMPSP.NAPSP.PCAscore.cindexscore.iAUCTimeSurvProbzt

Dependencies:backportsbase64encBolstad2bslibcachemcheckmatecliclustercmprskcodetoolscolorspacedata.tablediagramdigestdoParallelevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsfuturefuture.applyggplot2glmnetglobalsgluegridExtragtablehamlethighrHmischtmlTablehtmltoolshtmlwidgetsimputeisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvmagrittrMASSMatrixMatrixModelsmemoisemetsmgcvmimemultcompmunsellmvtnormnlmennetnumDerivparallellypecpillarpkgconfigplotrixpolsplinepracmaprodlimprogressrPublishquantregR6rangerrappdirsRColorBrewerRcppRcppArmadilloRcppEigenriskRegressionrlangrmarkdownrmsrpartrstudioapisandwichsassscalesshapeSparseMSQUAREMstringistringrsurvivalTH.datatibbletimeregtimeROCtinytexutf8vctrsviridisviridisLitewithrxfunyamlzoo

User guide to the ePCR R-package

Rendered fromePCR_guide.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2024-02-19
Started: 2023-07-29

Readme and manuals

Help Manual

Help pageTopics
Bootstrapped testing of regression coefficients in a penalized modelbootstrapRegCoefs
Conform the dimensions of a new input data matrix to a readily fitted PEP or PSP objectconforminput
Function that creates customized cross-validation foldscv
Cross-validation runs for risk predition at a single value of alphacv.alpha
Cross-validation runs for risk predition for a grid of predetermined alpha values and their conditional lambda valuescv.grid
FIMM-UTU DREAM winning implementation of an ensemble of Penalized Cox Regression models for mCPRC research (ePCR)DREAM
Ensemble Penalized Cox Regression Modeling for Overall Survival and Time-to-Event Prediction in Advanced Prostate CancerePCR
Plot a heatmap of the prediction performance statistic as a function of lambda and alpha combinationsheatcv
Integrate the area over/under the regularization path of a penalized regression modelintegrateRegCurve
Compute all pairwise interactions between the columns of a data matrixinteract.all
Compute a chosen set of pairwise interactions between two sets of columns in a data matrixinteract.part
Compute mean of predicted risk ranks for an ePCR ensemblemeanrank
Cox-Oakes extension of the Nelson-Aalen estimates for a Cox modelNelsonAalen
Normalize ensemble risk scores to ranks and then to uniform rangenormriskrank
Penalized Ensemble Predictor (PEP) S4-class ensemble consisting of individual PSP-membersPEP-class
PEP-methodsPEP-methods predict,PEP-method print,PEP-method
Penalized Single Predictor (PSP) S4-class as a member of PEP-ensemblesPSP-class
PSP-methodscoef,PSP-method plot plot,PSP,ANY-method plot,PSP-method predict,PSP-method print,PSP-method PSP-methods PSP.BOX PSP.BOX,PSP,ANY-method PSP.BOX,PSP-method PSP.CSP PSP.CSP,PSP,ANY-method PSP.CSP,PSP-method PSP.KM PSP.KM,PSP,ANY-method PSP.KM,PSP-method PSP.NA PSP.NA,PSP,ANY-method PSP.NA,PSP-method PSP.PCA PSP.PCA,PSP,ANY-method PSP.PCA,PSP-method
Scoring function for evaluating survival prediction through concordance index (c-index)score.cindex
Scoring function for evaluating survival prediction by time-wise integrated AUCscore.iAUC
Predict cumulative survival probabilities for new data at given time pointsTimeSurvProb
ePCR model fitted to the Turku University Hospital cohorts (all features)TYKS
ePCR model fitted to the Turku University Hospital cohorts (features derived from text mining only)TYKS_reduced
TYKSSIMU - simulated data matrices and survival responses from Turku University HospitalTYKSSIMU xMEDISIMU xTEXTSIMU yMEDISIMU yTEXTSIMU
Extended function for z-transformation, filling non-finite values and changes column names at willzt