- recipe bioconductor-beer
Bayesian Enrichment Estimation in R
MIT + file LICENSE
BEER implements a Bayesian model for analyzing phage-immunoprecipitation sequencing (PhIP-seq) data. Given a PhIPData object, BEER returns posterior probabilities of enriched antibody responses, point estimates for the relative fold-change in comparison to negative control samples, and more. Additionally, BEER provides a convenient implementation for using edgeR to identify enriched antibody responses.
- package bioconductor-beer¶
- depends bioconductor-biocparallel:
- depends bioconductor-edger:
- depends bioconductor-phipdata:
- depends bioconductor-summarizedexperiment:
- depends r-base:
- depends r-cli:
- depends r-progressr:
- depends r-rjags:
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-beer and update with:: mamba update bioconductor-beer
To create a new environment, run:
mamba create --name myenvname bioconductor-beer
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-beer:<tag> (see `bioconductor-beer/tags`_ for valid values for ``<tag>``)