recipe bioconductor-cogaps

Coordinated Gene Activity in Pattern Sets

Homepage:

https://bioconductor.org/packages/3.16/bioc/html/CoGAPS.html

License:

BSD_3_clause + file LICENSE

Recipe:

/bioconductor-cogaps/meta.yaml

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:

3.18.0-0,  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, 

3.18.0-0,  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 >=1.32.0,<1.33.0

• bioconductor-rhdf5 >=2.42.0,<2.43.0

• bioconductor-s4vectors >=0.36.0,<0.37.0

• bioconductor-singlecellexperiment >=1.20.0,<1.21.0

• bioconductor-summarizedexperiment >=1.28.0,<1.29.0

• libblas >=3.9.0,<4.0a0

• libgcc-ng >=12

• liblapack >=3.9.0,<4.0a0

• libstdcxx-ng >=12

• r-base >=4.2,<4.3.0a0

• r-bh

• r-cluster

• r-gplots

• r-rcolorbrewer

• r-rcpp

Required By:

• bioconductor-ataccogaps

• bioconductor-projectr

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-cogaps

and update with:

conda update bioconductor-cogaps

or use the docker container:

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

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

Download stats

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