-
recipe
bioconductor-cnvpanelizer¶ 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.
- Homepage
https://bioconductor.org/packages/3.9/bioc/html/CNVPanelizer.html
- License
GPL-3
- Recipe
- Links
biotools: cnvpanelizer, doi: 10.1038/nmeth.3252
-
package
bioconductor-cnvpanelizer¶ 
- Versions
1.14.0-0, 1.12.0-0, 1.8.0-0
- Depends bioconductor-exomecopy
>=1.28.0,<1.29.0
- Depends bioconductor-genomeinfodb
>=1.18.0,<1.19.0
- Depends bioconductor-genomicranges
>=1.34.0,<1.35.0
- Depends bioconductor-iranges
>=2.16.0,<2.17.0
- Depends bioconductor-noiseq
>=2.26.0,<2.27.0
- Depends bioconductor-rsamtools
>=1.34.0,<1.35.0
- Depends bioconductor-s4vectors
>=0.20.0,<0.21.0
- Depends r-base
>=3.5.1,<3.5.2.0a0
- Depends r-foreach
- Depends r-ggplot2
- Depends r-gplots
- Depends r-openxlsx
- Depends r-plyr
- Depends r-reshape2
- Depends r-shiny
- Depends r-shinyfiles
- Depends r-shinyjs
- Depends r-stringr
- Depends r-testthat
- Requirements
Installation
With an activated Bioconda channel (see 2. Set up channels), install with:
conda install bioconductor-cnvpanelizer
and update with:
conda update bioconductor-cnvpanelizer
or use the docker container:
docker pull quay.io/biocontainers/bioconductor-cnvpanelizer:<tag>
(see bioconductor-cnvpanelizer/tags for valid values for
<tag>)
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-cnvpanelizer/README.html)