Package Recipe 'bioconductor-cancerclass'

recipe bioconductor-cancerclass

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

Homepage:: https://bioconductor.org/packages/3.16/bioc/html/cancerclass.html
License:: GPL 3
Recipe:: /bioconductor-cancerclass/meta.yaml

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 bioconductor-cancerclass¶

Versions:

1.42.0-0, 1.38.0-2, 1.38.0-1, 1.38.0-0, 1.36.0-0, 1.34.0-1, 1.34.0-0, 1.32.0-0, 1.30.0-0,

1.42.0-0, 1.38.0-2, 1.38.0-1, 1.38.0-0, 1.36.0-0, 1.34.0-1, 1.34.0-0, 1.32.0-0, 1.30.0-0, 1.28.0-1, 1.26.0-0

Depends:

bioconductor-biobase >=2.58.0,<2.59.0
libblas >=3.9.0,<4.0a0
libgcc-ng >=12
liblapack >=3.9.0,<4.0a0
r-base >=4.2,<4.3.0a0
r-binom

Required By:

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-cancerclass

and update with:

conda update bioconductor-cancerclass

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-cancerclass:<tag>

(see bioconductor-cancerclass/tags for valid values for <tag>)

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-cancerclass/README.html)