- recipe bioconductor-spqn
Spatial quantile normalization
- Homepage:
- License:
Artistic-2.0
- Recipe:
The spqn package implements spatial quantile normalization (SpQN). This method was developed to remove a mean-correlation relationship in correlation matrices built from gene expression data. It can serve as pre-processing step prior to a co-expression analysis.
- package bioconductor-spqn¶
- versions:
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 bioconductor-biocgenerics:
>=0.48.0,<0.49.0
- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0
- depends r-base:
>=4.3,<4.4.0a0
- depends r-ggplot2:
- depends r-ggridges:
- depends r-matrixstats:
- 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-spqn and update with:: mamba update bioconductor-spqn
To create a new environment, run:
mamba create --name myenvname bioconductor-spqn
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-spqn:<tag> (see `bioconductor-spqn/tags`_ for valid values for ``<tag>``)
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-spqn/README.html)