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beer

Bayesian Enrichment Estimation in R

Bioconductor version: 3.23 · Package version: 1.15.1

Other Bioconductor versions

devel is the development version; release is the current stable one.

3.24 (devel), 3.23 (release)

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.

DOI: 10.18129/B9.bioc.beer

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("beer")

Details

MaintainerAthena Chen <achen70@jhu.edu>
AuthorAthena Chen [aut, cre] (ORCID: <https://orcid.org/0000-0001-6900-2264>), Rob Scharpf [aut], Ingo Ruczinski [aut]
LicenseMIT + file LICENSE
URLhttps://github.com/athchen/beer/
Bug Reportshttps://github.com/athchen/beer/issues
System RequirementsJAGS (4.3.0)
Source branchRELEASE_3_23
Build report Bioconductor build system, r-universe
biocViewsBayesian, Coverage, Sequencing, Software, StatisticalMethod
Package Short Url https://bioconductor.org/packages/beer/

Citation

From within R, enter citation("beer"):

Athena Chen, Rob Scharpf, Ingo Ruczinski. beer: Bayesian Enrichment Estimation in R. doi:10.18129/B9.bioc.beer, R package version 1.15.1, https://bioconductor.org/packages/beer.

Generated from the package metadata; it may differ from the package's own citation.

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagebeer_1.15.1.tar.gz
Windows binary (x86_64)beer_1.15.1.zip
macOS binary (arm64)beer_1.15.1.tgz
macOS binary (x86_64)beer_1.15.1.tgz
Dependencies

Depends: R (>= 4.2.0), PhIPData (>= 1.1.1), rjags

Imports: cli, edgeR, BiocParallel, methods, progressr, stats, SummarizedExperiment, utils

Suggests: testthat (>= 3.0.0), BiocStyle, covr, codetools, knitr, rmarkdown, dplyr, ggplot2, spelling