recipe r-dndscv

dN/dS methods to quantify selection in cancer and somatic evolution.

Homepage:

https://github.com/im3sanger/dndscv

Documentation:

https://htmlpreview.github.io/?http://github.com/im3sanger/dndscv/blob/master/vignettes/dNdScv.html

License:

GPL3 / GPL-3.0-or-later

Recipe:

/r-dndscv/meta.yaml

Description: This package contains functions for studying selection on coding sequences using a Poisson implementation of dN/dS. A Poisson model of dN/dS facilitates the study of selection beyond traditional codon models, including complex context-dependent mutation effects and selection on nonsense and splice site mutations. This model is best suited for resequencing studies, with very low density of mutations per base pair. The model was initially developed for cancer genome sequencing studies, and specific functions are provided to perform driver gene discovery using the dNdScv method on human cancer genomic data.

package r-dndscv

versions:

0.1.0-0

depends bioconductor-biostrings:

depends bioconductor-genomicranges:

depends bioconductor-iranges:

depends bioconductor-rsamtools:

depends r-base:

>=4.4,<4.5.0a0

depends r-mass:

depends r-plyr:

depends r-poilog:

depends r-seqinr:

requirements:

additional platforms:

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 r-dndscv

and update with::

   mamba update r-dndscv

To create a new environment, run:

mamba create --name myenvname r-dndscv

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/r-dndscv:<tag>

(see `r-dndscv/tags`_ for valid values for ``<tag>``)

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