recipe bioconductor-purecn

Copy number calling and SNV classification using targeted short read sequencing

Homepage:

https://bioconductor.org/packages/3.17/bioc/html/PureCN.html

License:

Artistic-2.0

Recipe:

/bioconductor-purecn/meta.yaml

Links:

biotools: purecn

This package estimates tumor purity, copy number, and loss of heterozygosity (LOH), and classifies single nucleotide variants (SNVs) by somatic status and clonality. PureCN is designed for targeted short read sequencing data, integrates well with standard somatic variant detection and copy number pipelines, and has support for tumor samples without matching normal samples.

package bioconductor-purecn

versions:

2.6.4-0,  2.4.0-1,  2.4.0-0,  2.0.2-0,  2.0.1-0,  1.22.1-0,  1.20.0-1,  1.20.0-0,  1.18.1-0, 

2.6.4-0,  2.4.0-1,  2.4.0-0,  2.0.2-0,  2.0.1-0,  1.22.1-0,  1.20.0-1,  1.20.0-0,  1.18.1-0,  1.18.0-0,  1.16.0-2,  1.16.0-1,  1.16.0-0,  1.14.2-0,  1.14.0-0,  1.13.1-2,  1.12.1-0,  1.11.20-2,  1.11.20-1,  1.11.13-1,  1.11.13-0,  1.8.0-0,  1.6.3-0

depends bioconductor-biobase:

>=2.60.0,<2.61.0

depends bioconductor-biocgenerics:

>=0.46.0,<0.47.0

depends bioconductor-biostrings:

>=2.68.0,<2.69.0

depends bioconductor-dnacopy:

>=1.74.0,<1.75.0

depends bioconductor-genomeinfodb:

>=1.36.0,<1.37.0

depends bioconductor-genomicfeatures:

>=1.52.0,<1.53.0

depends bioconductor-genomicranges:

>=1.52.0,<1.53.0

depends bioconductor-iranges:

>=2.34.0,<2.35.0

depends bioconductor-rhdf5:

>=2.44.0,<2.45.0

depends bioconductor-rsamtools:

>=2.16.0,<2.17.0

depends bioconductor-rtracklayer:

>=1.60.0,<1.61.0

depends bioconductor-s4vectors:

>=0.38.0,<0.39.0

depends bioconductor-summarizedexperiment:

>=1.30.0,<1.31.0

depends bioconductor-variantannotation:

>=1.46.0,<1.47.0

depends r-base:

>=4.3,<4.4.0a0

depends r-data.table:

depends r-futile.logger:

depends r-ggplot2:

depends r-gridextra:

depends r-matrix:

depends r-mclust:

depends r-rcolorbrewer:

depends r-vgam:

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-purecn

and update with::

   mamba update bioconductor-purecn

To create a new environment, run:

mamba create --name myenvname bioconductor-purecn

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/bioconductor-purecn:<tag>

(see `bioconductor-purecn/tags`_ for valid values for ``<tag>``)

Download stats

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