bioconductor-cnvpanelizer

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A method that allows for the use of a collection of non-matched normal tissue samples. Our approach uses a non-parametric bootstrap subsampling of the available reference samples to estimate the distribution of read counts from targeted sequencing. As inspired by random forest, this is combined with a procedure that subsamples the amplicons associated with each of the targeted genes. The obtained information allows us to reliably classify the copy number aberrations on the gene level.

Home http://bioconductor.org/packages/3.7/bioc/html/CNVPanelizer.html
Versions 1.12.0, 1.8.0
License GPL-3
Recipe https://github.com/bioconda/bioconda-recipes/tree/master/recipes/bioconductor-cnvpanelizer
Links biotools: cnvpanelizer, doi: 10.1038/nmeth.3252

Installation

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

conda install bioconductor-cnvpanelizer

and update with:

conda update bioconductor-cnvpanelizer

docker

A Docker container is available at https://quay.io/repository/biocontainers/bioconductor-cnvpanelizer.