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  "Title": "Bayesian Enrichment Estimation in R",
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  "Description": "BEER implements a Bayesian model for analyzing\nphage-immunoprecipitation sequencing (PhIP-seq) data. Given a\nPhIPData object, BEER returns posterior probabilities of\nenriched antibody responses, point estimates for the relative\nfold-change in comparison to negative control samples, and\nmore. Additionally, BEER provides a convenient implementation\nfor using edgeR to identify enriched antibody responses.",
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  "Encoding": "UTF-8",
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  "biocViews": "Software, StatisticalMethod, Bayesian, Sequencing, Coverage",
  "URL": "https://github.com/athchen/beer/",
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  "Repository": "https://bioc-release.r-universe.dev",
  "Date/Publication": "2026-04-28 12:57:48 UTC",
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  "Author": "Athena Chen [aut, cre] (ORCID: <https://orcid.org/0000-0001-6900-2264>),\nRob Scharpf [aut],\nIngo Ruczinski [aut]",
  "Maintainer": "Athena Chen <achen70@jhu.edu>",
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      "page": "dot-beadsRREdgeR",
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    },
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      "title": "Run BEER for all samples",
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    },
    {
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    },
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      "page": "dot-edgeRBeadsQLF",
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        ".edgeRBeadsQLF"
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    {
      "page": "dot-getABEdgeR",
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    },
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    },
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      "page": "dot-getABMOM",
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    },
    {
      "page": "dot-getABMOMProp",
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      "topics": [
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      "topics": [
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      ]
    },
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      "page": "dot-guessEnrichedMLE",
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      ]
    },
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      "page": "dot-tidyAssayNames",
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    },
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    },
    {
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      "title": "Derive point estimates for c, pi, phi, and Z for a particular sample",
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