Package Recipe 'bioconductor-receptloss'

recipe bioconductor-receptloss

Unsupervised Identification of Genes with Expression Loss in Subsets of Tumors

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/receptLoss.html
License:: GPL-3 + file LICENSE
Recipe:: /bioconductor-receptloss/meta.yaml

receptLoss identifies genes whose expression is lost in subsets of tumors relative to normal tissue. It is particularly well-suited in cases where the number of normal tissue samples is small, as the distribution of gene expression in normal tissue samples is approximated by a Gaussian. Originally designed for identifying nuclear hormone receptor expression loss but can be applied transcriptome wide as well.

package bioconductor-receptloss¶

Versions:

1.18.0-0, 1.14.0-0, 1.12.0-0, 1.10.0-0, 1.6.0-0, 1.4.0-0, 1.2.0-1, 1.2.0-0, 1.0.0-0

Depends:

on bioconductor-summarizedexperiment >=1.36.0,<1.37.0
on r-base >=4.4,<4.5.0a0
on r-dplyr
on r-ggplot2
on r-magrittr
on r-tidyr

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-receptloss

to add into an existing workspace instead, run:

pixi add bioconductor-receptloss

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-receptloss

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-receptloss

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-receptloss:<tag>

(see bioconductor-receptloss/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-receptloss/README.html)