recipe bioconductor-bayesknockdown

A simple, fast Bayesian method for computing posterior probabilities for relationships between a single predictor variable and multiple potential outcome variables, incorporating prior probabilities of relationships. In the context of knockdown experiments, the predictor variable is the knocked-down gene, while the other genes are potential targets. Can also be used for differential expression/2-class data.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/BayesKnockdown.html

License

GPL-3

Recipe

/bioconductor-bayesknockdown/meta.yaml

package bioconductor-bayesknockdown

(downloads) docker_bioconductor-bayesknockdown

Versions

1.10.0-1, 1.8.0-0

Depends
Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-bayesknockdown

and update with:

conda update bioconductor-bayesknockdown

or use the docker container:

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

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