CPSM
Bioc currentCPSM: Cancer patient survival model
Release Lineage
Entered 3.21 · Apr 16, 2025
Current · Requires R 4.6
Description
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.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
11 11 exported
Complexity
12 avg / 25 max
Call network
11 nodes / 0 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
18,655
Files
91
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
11
Internal functions
0
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.07
testthat edition
3
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.5
System requirements
–
C++ standard
–
License
GPL-3 | file LICENSE
License flags
SPDX valid, not OSI
History
Versions
3
First release
2025-04-15
Latest release
2026-04-28
Avg cadence
189 days
Cold removal rate
–
Dep drift
7
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 99%
- Return-value docs
- 100%
- References docs
- 3%
Datasets
| Name | Class | Rows × Cols | Also in |
|---|---|---|---|
| Key_Clin_feature_list | data.frame | 4 × 1 | No other package |
| Key_Clin_features_with_PI_list | data.frame | 4 × 1 | No other package |
| Key_PI_list | data.frame | 1 × 1 | No other package |
| Key_univariate_features_list | data.frame | 2,391 × 1 | No other package |
| Key_univariate_features_with_Clin_list | data.frame | 2,394 × 1 | No other package |
| New_data | data.frame | 176 × 2,025 | No other package |
| Test_Clin | data.frame | 18 × 20 | No other package |
| Test_Norm_data | data.frame | 18 × 2,025 | No other package |
| Test_PI_data | data.frame | 18 × 57 | No other package |
| Test_Uni_sig_data | data.frame | 18 × 209 | No other package |
| Test_results | data.frame | 18 × 8 | No other package |
| Train_Clin | data.frame | 158 × 20 | No other package |
| Train_Data_Nomogram_input | data.frame | 158 × 34 | No other package |
| Train_Norm_data | data.frame | 158 × 2,025 | No other package |
| Train_PI_data | data.frame | 158 × 57 | No other package |
| Train_Uni_sig_data | data.frame | 158 × 209 | No other package |
| Train_results | data.frame | 158 × 8 | No other package |
| feature_list_for_Nomogram | data.frame | 6 × 1 | No other package |
| mean_median_survival_time_data | data.frame | 18 × 3 | No other package |
| survCurves_data | data.frame | 15 × 19 | No other package |
| test_FPKM | data.frame | 18 × 2,025 | No other package |
| train_FPKM | data.frame | 158 × 2,025 | No other package |
Topics
People
- Harpreet Kaur author maintainer
- Kevin Camphausen author
- Pijush Das author
- Uma Shankavaram author contributor
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("CPSM")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.