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.

Package details

AuthorJan Budczies, Daniel Kosztyla
Bioconductor views Cancer Classification Microarray Visualization
MaintainerDaniel Kosztyla <>
LicenseGPL 3
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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cancerclass documentation built on Nov. 8, 2020, 5:31 p.m.