Package: cancerclass 1.49.0

Daniel Kosztyla

cancerclass: Development and validation of diagnostic tests from high-dimensional molecular data

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.

Authors:Jan Budczies, Daniel Kosztyla

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cancerclass/json (API)

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

Peer review:

Datasets:

On BioConductor:cancerclass-1.49.0(bioc 3.20)cancerclass-1.48.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

18 exports 1.00 score 3 dependencies 1 mentions

Last updated 2 months agofrom:e945e63421

Exports:.initFoocalc.auccalc.rocfilterfitget.dget.d2get.lmget.ntrainilogitloonvalidateplotplot3dpredictpreparesummaryvalidate

Dependencies:binomBiobaseBiocGenerics

Cancerclass: An R package for development and validation of diagnostic tests from high-dimensional molecular data

Rendered fromvignette_cancerclass.Rnwusingutils::Sweaveon Jul 03 2024.

Last update: 2013-11-01
Started: 2013-11-01