cancerclass

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

Bioconductor version: Release (2.11)

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>

To install this package, start R and enter:

    source("http://bioconductor.org/biocLite.R")
    biocLite("cancerclass")

To cite this package in a publication, start R and enter:

    citation("cancerclass")

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