RUBIC detects recurrent copy number aberrations using copy number breaks, rather than recurrently amplified or deleted regions. This allows for a vastly simplified approach as recursive peak splitting procedures and repeated re-estimation of the background model are avoided. Furthermore, the false discovery rate is controlled on the level of called regions, rather than at the probe level.

Home http://ccb.nki.nl/software/
Versions 1.0.2, 1.0.3
License Apache-2.0
Recipe https://github.com/bioconda/bioconda-recipes/tree/master/recipes/r-rubic/1.0.2


With an activated Bioconda channel (see 2. Set up channels), install with:

conda install r-rubic

and update with:

conda update r-rubic


A Docker container is available at https://quay.io/repository/biocontainers/r-rubic.