Package: CPSM 1.5.0

Harpreet Kaur

CPSM: CPSM: Cancer patient survival model

CPSM provides a comprehensive computational pipeline for predicting survival probability and risk groups in cancer patients. The package includes steps for data preprocessing, training/test split, and normalization. It enables feature selection using univariate survival analysis and computes a LASSO-based prognostic index (PI) score. CPSM supports the development of predictive models using various feature sets and offers a suite of visualization tools, including survival curves based on predicted probabilities, barplots for predicted mean and median survival times, KM plots overlaid with individual survival predictions, and nomograms for estimating 1-, 3-, 5-, and 10-year survival probabilities. This makes CPSM a versatile tool for survival analysis in cancer research.

Authors:Harpreet Kaur [aut, cre], Pijush Das [aut], Kevin Camphausen [aut], Uma Shankavaram [aut, ctb]

CPSM_1.5.0.tar.gz
CPSM_1.5.0.zip(r-4.7)CPSM_1.5.0.zip(r-4.6)CPSM_1.5.0.zip(r-4.5)
CPSM_1.5.0.tgz(r-4.6-any)CPSM_1.5.0.tgz(r-4.5-any)
CPSM_1.5.0.tar.gz(r-4.7-any)CPSM_1.5.0.tar.gz(r-4.6-any)
CPSM_1.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CPSM/json (API)
NEWS

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

Bug tracker:https://github.com/hks5august/cpsm/issues

Datasets:

On BioConductor:CPSM-1.5.0(bioc 3.24)CPSM-1.4.0(bioc 3.23)

normalizationsurvivalgeneexpressionpreprocessingfeatureextractionsoftwarevisualization

5.04 score 2 stars 6 scripts 256 downloads 11 exports 198 dependencies

Last updated from:6f31a19ed8. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE210
linux-devel-x86_64OK474
source / vignettesOK473
linux-release-x86_64OK447
macos-release-arm64OK269
macos-oldrel-arm64OK211
windows-develOK375
windows-releaseOK354
windows-oldrelOK369
wasm-releaseOK173

Exports:data_process_fkm_overlay_plot_fLasso_PI_scores_fmean_median_surv_barplot_fMTLR_pred_model_fNomogram_generate_fpredict_survival_risk_group_fsurv_curve_plots_ftr_test_ftrain_test_normalization_fUnivariate_sig_features_f

Dependencies:abindbackportsbase64encBiobaseBiocGenericsbitbit64bootbroombslibcachemcarcarDatacaretcheckmateclassclicliprclockclustercmprskcodetoolscolorspacecommonmarkcorrplotcowplotcpp11crayoncurldata.tabledata.treeDelayedArrayDerivdiagramDiagrammeRdigestdoBydoParalleldplyre1071evaluateexactRankTestsfarverfastmapfontawesomeforeachforecastforeignFormulafracdifffsfuturefuture.applygenericsGenomicRangesggfortifyggplot2ggpubrggrepelggsciggsignifggtextglmnetglobalsgluegowergridExtragridtextgtablehardhathighrHmischmshtmlTablehtmltoolshtmlwidgetsigraphipredIRangesisobanditeratorsjpegjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlitedownlme4lmtestlubridatemagrittrmarkdownMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmaxstatmemoisemetsmgcvmicrobenchmarkmimeminqaModelMetricsmodelrMTLRmultcompmvtnormnlmenloptrnnetnumDerivparallellypbkrtestpecpillarpkgconfigplotrixplyrpngpolsplinepolynompreprocessCoreprettyunitspROCprodlimprogressprogressrproxyPublishpurrrquantregR6randomForestSRCrangerrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadrrecipesreformulasreshape2riskRegressionrlangrmarkdownrmsrpartrstatixrstudioapiS4ArraysS4VectorsS7sandwichsassscalesSeqinfoshapeSparseArraySparseMsparsevctrsSQUAREMstringistringrSummarizedExperimentsurvivalSurvMetricssurvminerTH.datatibbletidyrtidyselecttimechangetimeDatetimeregtinytextzdburcautf8vctrsviridisLitevisNetworkvroomwithrxfunxml2XVectoryamlzoo

CPSM: Cancer patient survival model

Harpreet Kaur, Pijush Das, Kevin Camphausen, Uma Shankavaram

Rendered fromCPSM.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2026-01-30
Started: 2024-12-06

Readme and manuals

Help Manual

Help pageTopics
Data Processing functiondata_process_f
Example TCGA LGG FPKM dataExample_TCGA_LGG_FPKM_data
feature list for Nomogramfeature_list_for_Nomogram
Key Clin feature listKey_Clin_feature_list
Key Clin features with PI listKey_Clin_features_with_PI_list
Key PI listKey_PI_list
Key univariate features listKey_univariate_features_list
Key univariate features with Clin listKey_univariate_features_with_Clin_list
Overlay Kaplan-Meier Plot Functionkm_overlay_plot_f
Lasso-Based Prognostic Index CalculationLasso_PI_scores_f
Mean and Median Survival Bar Plotmean_median_surv_barplot_f
mean median survival time datamean_median_survival_time_data
MTLR Prediction Model FunctionMTLR_pred_model_f
New dataNew_data
Nomogram Generation FunctionNomogram_generate_f
Survival Risk Group Prediction Functionpredict_survival_risk_group_f
Generate Survival Curve Plotssurv_curve_plots_f
survCurves datasurvCurves_data
Test ClinTest_Clin
test FPKMtest_FPKM
Test Norm dataTest_Norm_data
Test PI dataTest_PI_data
Test Results for Survival PredictionTest_results
Test Uni sig dataTest_Uni_sig_data
Train-Test Split Functiontr_test_f
Train ClinTrain_Clin
Train Data Nomogram inputTrain_Data_Nomogram_input
train FPKMtrain_FPKM
Train Norm dataTrain_Norm_data
Train PI dataTrain_PI_data
Training Results for Survival PredictionTrain_results
Train-Test Data Normalization Functiontrain_test_normalization_f
Train Uni sig dataTrain_Uni_sig_data
Perform Univariate Survival AnalysisUnivariate_sig_features_f