Package Recipe 'bioconductor-zygositypredictor'

recipe bioconductor-zygositypredictor

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

Homepage:: https://bioconductor.org/packages/3.20/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¶

Versions:

1.10.0-0, 1.6.0-0, 1.2.0-0, 1.0.3-0

Depends:

on bioconductor-delayedarray >=0.36.0,<0.37.0
on bioconductor-genomicalignments >=1.46.0,<1.47.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-rsamtools >=2.26.0,<2.27.0
on bioconductor-variantannotation >=1.56.0,<1.57.0
on r-base >=4.5,<4.6.0a0
on r-dplyr
on r-igraph
on r-knitr
on r-magrittr
on r-purrr
on r-readr
on r-rlang
on r-stringr
on r-tibble

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-zygositypredictor

to add into an existing workspace instead, run:

pixi add bioconductor-zygositypredictor

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-zygositypredictor

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-zygositypredictor

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-zygositypredictor/README.html)