recipe bioconductor-zygositypredictor

Package for prediction of zygosity for variants/genes in NGS data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/ZygosityPredictor.html

License:

GPL-2

Recipe:

/bioconductor-zygositypredictor/meta.yaml

The ZygosityPredictor allows to predict how many copies of a gene are affected by small variants. In addition to the basic calculations of the affected copy number of a variant, the Zygosity-Predictor can integrate the influence of several variants on a gene and ultimately make a statement if and how many wild-type copies of the gene are left. This information proves to be of particular use in the context of translational medicine. For example, in cancer genomes, the Zygosity-Predictor can address whether unmutated copies of tumor-suppressor genes are present. Beyond this, it is possible to make this statement for all genes of an organism. The Zygosity-Predictor was primarily developed to handle SNVs and INDELs (later addressed as small-variants) of somatic and germline origin. In order not to overlook severe effects outside of the small-variant context, it has been extended with the assessment of large scale deletions, which cause losses of whole genes or parts of them.

package bioconductor-zygositypredictor

(downloads) docker_bioconductor-zygositypredictor

versions:

1.2.0-01.0.3-0

depends bioconductor-delayedarray:

>=0.28.0,<0.29.0

depends bioconductor-genomicalignments:

>=1.38.0,<1.39.0

depends bioconductor-genomicranges:

>=1.54.0,<1.55.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-rsamtools:

>=2.18.0,<2.19.0

depends bioconductor-variantannotation:

>=1.48.0,<1.49.0

depends r-base:

>=4.3,<4.4.0a0

depends r-dplyr:

depends r-igraph:

depends r-purrr:

depends r-stringr:

depends r-tibble:

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 bioconductor-zygositypredictor

and update with::

   mamba update bioconductor-zygositypredictor

To create a new environment, run:

mamba create --name myenvname bioconductor-zygositypredictor

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-zygositypredictor:<tag>

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

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