Package: CPSM 0.99.7

Harpreet Kaur

CPSM: CPSM: Cancer patient survival model

The CPSM package provides a comprehensive computational pipeline for predicting the survival probability of cancer patients. It offers a series of steps including data processing, splitting data into training and test subsets, and normalization of data. The package enables the selection of significant features based on univariate survival analysis and generates a LASSO prognostic index score. It supports the development of predictive models for survival probability using various features and provides visualization tools to draw survival curves based on predicted survival probabilities. Additionally, SPM includes functionalities for generating bar plots that depict the predicted mean and median survival times of patients, making it a versatile tool for survival analysis in cancer research.

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

CPSM_0.99.7.tar.gz
CPSM_0.99.7.zip(r-4.5)CPSM_0.99.7.zip(r-4.4)
CPSM_0.99.7.tgz(r-4.5-any)CPSM_0.99.7.tgz(r-4.4-any)
CPSM_0.99.7.tar.gz(r-4.5-noble)CPSM_0.99.7.tar.gz(r-4.4-noble)
CPSM_0.99.7.tgz(r-4.4-emscripten)
CPSM.pdf |CPSM.html✨
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:

Example_TCGA_LGG_FPKM_data - Example TCGA LGG FPKM data
Key_Clin_feature_list - Key Clin feature list
Key_Clin_features_with_PI_list - Key Clin features with PI list
Key_PI_list - Key PI list
Key_univariate_features_list - Key univariate features list
Key_univariate_features_with_Clin_list - Key univariate features with Clin list
New_data - New data
Test_Clin - Test Clin
Test_Norm_data - Test Norm data
Test_PI_data - Test PI data
Test_Uni_sig_data - Test Uni sig data
Train_Clin - Train Clin
Train_Data_Nomogram_input - Train Data Nomogram input
Train_Norm_data - Train Norm data
Train_PI_data - Train PI data
Train_Uni_sig_data - Train Uni sig data
feature_list_for_Nomogram - Feature list for Nomogram
mean_median_survival_time_data - Mean median survival time data
survCurves_data - SurvCurves data
test_FPKM - Test FPKM
train_FPKM - Train FPKM

On BioConductor:CPSM-0.99.7(bioc 3.21)

geneexpression normalization survival

3.90 score 9 exports 183 dependencies

Last updated 1 days agofrom:f9ecfc0ceb. Checks:3 ERROR, 4 WARNING. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	FAIL	Mar 12 2025
R-4.5-win	WARNING	Mar 12 2025
R-4.5-mac	WARNING	Mar 12 2025
R-4.5-linux	ERROR	Mar 12 2025
R-4.4-win	WARNING	Mar 12 2025
R-4.4-mac	WARNING	Mar 12 2025
R-4.4-linux	ERROR	Mar 12 2025

Exports:data_process_f Lasso_PI_scores_f mean_median_surv_barplot_f MTLR_pred_model_f Nomogram_generate_f surv_curve_plots_f tr_test_f train_test_normalization_f Univariate_sig_features_f

Dependencies:abind askpass backports base64enc Biobase BiocGenerics bitops boot broom bslib cachem car carData caTools checkmate cli cluster cmprsk codetools colorspace commonmark corrplot cowplot cpp11 crayon curl data.table DelayedArray Deriv diagram digest doBy doParallel dplyr evaluate exactRankTests fansi farver fastmap fontawesome foreach foreign Formula fs future future.apply generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggfortify ggplot2 ggpubr ggrepel ggsci ggsignif ggtext glmnet globals glue gplots gridExtra gridtext gtable gtools highr Hmisc htmlTable htmltools htmlwidgets httr IRanges isoband iterators jpeg jquerylib jsonlite KernSmooth km.ci KMsurv knitr labeling lattice lava lifecycle listenv lme4 magrittr markdown MASS Matrix MatrixGenerics MatrixModels matrixStats maxstat memoise mets mgcv microbenchmark mime minqa modelr MTLR multcomp munsell mvtnorm nlme nloptr nnet numDeriv openssl parallelly pbkrtest pec pillar pkgconfig plotrix plyr png polspline polynom preprocessCore prodlim progressr Publish purrr quantreg R6 ranger rappdirs rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack reformulas reshape2 riskRegression rlang rmarkdown rms ROCR rpart rstatix rstudioapi S4Arrays S4Vectors sandwich sass scales shape SparseArray SparseM SQUAREM stringi stringr SummarizedExperiment survival survivalROC survminer survMisc svglite sys systemfonts TH.data tibble tidyr tidyselect timereg tinytex UCSC.utils utf8 vctrs viridis viridisLite withr xfun xml2 xtable XVector yaml zoo

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Help page	Topics
Data Processing f	data_process_f
Example TCGA LGG FPKM data	Example_TCGA_LGG_FPKM_data
feature list for Nomogram	feature_list_for_Nomogram
Key Clin feature list	Key_Clin_feature_list
Key Clin features with PI list	Key_Clin_features_with_PI_list
Key PI list	Key_PI_list
Key univariate features list	Key_univariate_features_list
Key univariate features with Clin list	Key_univariate_features_with_Clin_list
Lasso-Based Prognostic Index Calculation	Lasso_PI_scores_f
Mean and Median Survival Bar Plot	mean_median_surv_barplot_f
mean median survival time data	mean_median_survival_time_data
MTLR Prediction Model Function	MTLR_pred_model_f
New data	New_data
Nomogram Generation Function	Nomogram_generate_f
Generate Survival Curve Plots	surv_curve_plots_f
survCurves data	survCurves_data
Test Clin	Test_Clin
test FPKM	test_FPKM
Test Norm data	Test_Norm_data
Test PI data	Test_PI_data
Test Uni sig data	Test_Uni_sig_data
Train-Test Split Function	tr_test_f
Train Clin	Train_Clin
Train Data Nomogram input	Train_Data_Nomogram_input
train FPKM	train_FPKM
Train Norm data	Train_Norm_data
Train PI data	Train_PI_data
Train-Test Data Normalization Function	train_test_normalization_f
Train Uni sig data	Train_Uni_sig_data
Perform Univariate Survival Analysis	Univariate_sig_features_f

Package: CPSM 0.99.7

CPSM: CPSM: Cancer patient survival model

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