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

/bioconductor-cnvpanelizer/meta.yaml

Links

biotools: cnvpanelizer, doi: 10.1038/nmeth.3252

package bioconductor-cnvpanelizer

(downloads) docker_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>)