- recipe bioconductor-cogaps
Coordinated Gene Activity in Pattern Sets
- Homepage:
https://bioconductor.org/packages/3.20/bioc/html/CoGAPS.html
- License:
BSD_3_clause + file LICENSE
- Recipe:
Coordinated Gene Activity in Pattern Sets (CoGAPS) implements a Bayesian MCMC matrix factorization algorithm, GAPS, and links it to gene set statistic methods to infer biological process activity. It can be used to perform sparse matrix factorization on any data, and when this data represents biomolecules, to do gene set analysis.
- package bioconductor-cogaps¶
- versions:
3.26.0-0,3.22.0-0,3.19.1-0,3.18.0-1,3.18.0-0,3.14.0-2,3.14.0-1,3.14.0-0,3.12.0-0,3.26.0-0,3.22.0-0,3.19.1-0,3.18.0-1,3.18.0-0,3.14.0-2,3.14.0-1,3.14.0-0,3.12.0-0,3.10.0-1,3.10.0-0,3.8.0-0,3.6.0-0,3.4.1-0,3.2.1-0- depends bioconductor-biocparallel:
>=1.40.0,<1.41.0- depends bioconductor-biocparallel:
>=1.40.0,<1.41.0a0- depends bioconductor-fgsea:
>=1.32.0,<1.33.0- depends bioconductor-fgsea:
>=1.32.0,<1.33.0a0- depends bioconductor-rhdf5:
>=2.50.0,<2.51.0- depends bioconductor-rhdf5:
>=2.50.0,<2.51.0a0- depends bioconductor-s4vectors:
>=0.44.0,<0.45.0- depends bioconductor-s4vectors:
>=0.44.0,<0.45.0a0- depends bioconductor-singlecellexperiment:
>=1.28.0,<1.29.0- depends bioconductor-singlecellexperiment:
>=1.28.0,<1.29.0a0- depends bioconductor-summarizedexperiment:
>=1.36.0,<1.37.0- depends bioconductor-summarizedexperiment:
>=1.36.0,<1.37.0a0- depends libblas:
>=3.9.0,<4.0a0- depends libgcc:
>=13- depends liblapack:
>=3.9.0,<4.0a0- depends libstdcxx:
>=13- depends r-base:
>=4.4,<4.5.0a0- depends r-bh:
- depends r-cluster:
- depends r-dplyr:
- depends r-forcats:
- depends r-ggplot2:
- depends r-gplots:
- depends r-rcolorbrewer:
- depends r-rcpp:
- 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-cogaps and update with:: mamba update bioconductor-cogaps
To create a new environment, run:
mamba create --name myenvname bioconductor-cogaps
with
myenvnamebeing 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-cogaps:<tag> (see `bioconductor-cogaps/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-cogaps/README.html)
