This is the development version of CPSM; for the stable release version, see CPSM.
CPSM: Cancer patient survival modelBioconductor version: Development (3.22)
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.
Author: Harpreet Kaur [aut, cre] ORCID: 0000-0003-0421-8341 , Pijush Das [aut], Kevin Camphausen [aut], Uma Shankavaram [aut]
Maintainer: Harpreet Kaur <hks04180 at gmail.com>
Citation (from within R, entercitation("CPSM")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("CPSM")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("CPSM")Follow Installation instructions to use this package in your R session.
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