recipe bioconductor-cancerclass

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.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/cancerclass.html

License

GPL 3

Recipe

/bioconductor-cancerclass/meta.yaml

package bioconductor-cancerclass

(downloads) docker_bioconductor-cancerclass

Versions

1.26.0-0

Depends
Required By

Installation

With an activated Bioconda channel (see 2. 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>)