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.
How to install beer?
biomate-ai/biomate-bioconductor-kb/beer
$npx -y skills add biomate-ai/biomate-bioconductor-kb --skill beerInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/biomate-ai/biomate-bioconductor-kb" --skill "biomate-ai/biomate-bioconductor-kb/beer"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/biomate-ai/biomate-bioconductor-kb" that are relevant to the current task. Run `npx skills add "https://github.com/biomate-ai/biomate-bioconductor-kb"` and select the relevant skills, then follow their instructions.
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