Bioconductor version: Release (3.15)
The classification protocol starts with a feature selection step and continues with nearest-centroid classification. The accurarcy of the predictor can be evaluated using training and test set validation, leave-one-out cross-validation or in a multiple random validation protocol. Methods for calculation and visualization of continuous prediction scores allow to balance sensitivity and specificity and define a cutoff value according to clinical requirements.
Author: Jan Budczies, Daniel Kosztyla
Maintainer: Daniel Kosztyla <danielkossi at hotmail.com>
Citation (from within R,
enter citation("cancerclass")
):
To install this package, start R (version "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("cancerclass")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("cancerclass")
R Script | Cancerclass: An R package for development and validation of diagnostic tests from high-dimensional molecular data | |
Reference Manual |
biocViews | Cancer, Classification, Microarray, Software, Visualization |
Version | 1.40.0 |
In Bioconductor since | BioC 2.11 (R-2.15) (10 years) |
License | GPL 3 |
Depends | R (>= 2.14.0), Biobase, binom, methods, stats |
Imports | |
LinkingTo | |
Suggests | cancerdata |
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Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | cancerclass_1.40.0.tar.gz |
Windows Binary | cancerclass_1.40.0.zip (64-bit only) |
macOS Binary (x86_64) | cancerclass_1.40.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/cancerclass |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/cancerclass |
Package Short Url | https://bioconductor.org/packages/cancerclass/ |
Package Downloads Report | Download Stats |
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