{
  "_id": "6a1ac8451d7bb097a09dc0ae",
  "Package": "limpa",
  "Version": "1.5.0",
  "Date": "2026-04-26",
  "Title": "Quantification and Differential Analysis of Proteomics Data",
  "Description": "Quantification and differential analysis of\nmass-spectrometry proteomics data, with probabilistic recovery\nof information from missing values. Avoids the need for\nimputation. Estimates the detection probability curve (DPC),\nwhich relates the probability of successful detection to the\nunderlying log-intensity of each precursor ion, and uses it to\nincorporate missing values into protein quantification and into\nsubsequent differential expression analyses. The package\nproduces objects suitable for downstream analysis in limma. The\npackage accepts precursor (or peptide) intensities including\nmissing values and produces complete protein quantifications\nwithout the need for imputation. The uncertainty of the protein\nquantifications is propagated through to the limma analyses\nusing variance modeling and precision weights, ensuring\naccurate error rate control. The analysis pipeline can\nalternatively work with PTM or protein level data. The package\nname \"limpa\" is an acronym for \"Linear Models for Proteomics\nData\".",
  "Authors@R": "c(person(\"Mengbo\", \"Li\",\nemail = \"li.me@wehi.edu.au\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-9666-5810\")),\nperson(\"Pedro\", \"Baldoni\",\nemail = \"baldoni.p@wehi.edu.au\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0002-9510-8326\")),\nperson(\"Gordon\", \"Smyth\",\nemail = \"smyth@wehi.edu.au\",\nrole = c(\"cre\", \"aut\"),\ncomment = c(ORCID = \"0000-0001-9221-2892\")))",
  "License": "GPL (>=2)",
  "VignetteBuilder": "knitr",
  "URL": "https://github.com/SmythLab/limpa",
  "biocViews": "Bayesian, BiologicalQuestion, DataImport,\nDifferentialExpression, GeneExpression, MassSpectrometry,\nPreprocessing, Proteomics, Regression, Software",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 13:04:41 UTC",
  "RemoteUrl": "https://github.com/bioc/limpa",
  "RemoteRef": "HEAD",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-30 07:48:56 UTC",
    "User": "root"
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  "Author": "Mengbo Li [aut] (ORCID: <https://orcid.org/0000-0002-9666-5810>),\nPedro Baldoni [ctb] (ORCID: <https://orcid.org/0000-0002-9510-8326>),\nGordon Smyth [cre, aut] (ORCID:\n<https://orcid.org/0000-0001-9221-2892>)",
  "Maintainer": "Gordon Smyth <smyth@wehi.edu.au>",
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  "_user": "bioc",
  "_type": "src",
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  "_created": "2026-05-30T07:48:56.000Z",
  "_published": "2026-05-30T11:21:41.479Z",
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    "filterNonProteotypicPeptides.EList",
    "filterNonProteotypicPeptides.EListRaw",
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    "plotAveVsMis",
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    "plotMDSUsingSEs",
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    "plotPeptides.EList",
    "plotProtein",
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    "pztbinom",
    "pztbinomSameSizeLogitPBothTails",
    "readDIANN",
    "readFragPipe",
    "readMaxQuant",
    "readSpectronaut",
    "readSpectronautRunInfo",
    "removeNARows",
    "removeNARows.default",
    "removeNARows.EList",
    "simCompleteDataCN",
    "simCompleteDataON",
    "simProteinDataSet",
    "voomaLmFitWithImputation"
  ],
  "_help": [
    {
      "page": "limpa-package",
      "title": "Linear Models for Proteomics Data (Accounting for Missing Values)",
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      ],
      "topics": [
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        "limpa"
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    },
    {
      "page": "completeMomentsON",
      "title": "Complete Distribution Moments from Observed Normal Model",
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      ],
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        "completeMomentsON"
      ]
    },
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      "title": "Detection Probability Curve",
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      ],
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      ]
    },
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      "title": "Detection Probability Curve Assuming Complete Normal Model",
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        "Detection probability curve"
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        "dpcCN"
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    },
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      "title": "Fit Linear Model With Precision Weights",
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    },
    {
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      "title": "Detection Probability Curve Assuming Observed Normal Model",
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        "Detection probability curve"
      ],
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        "dpcLegacy",
        "dpcON"
      ]
    },
    {
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      "title": "Quantify Proteins Using the DPC",
      "concept": [
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      ],
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        "dpcQuant",
        "dpcQuant.default",
        "dpcQuant.EList",
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    },
    {
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      ],
      "topics": [
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        "dpcQuantHyperparam"
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    },
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      "title": "Read Feature Intensities From a Long Format Report File Written By a Mass Spectrometry Quantification Tool",
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    },
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      "topics": [
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    },
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      "page": "readDIANN",
      "title": "Read Precursor Ion Intensities From DIA-NN Output",
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    },
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    },
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      "source": "limpa.Rmd",
      "filename": "limpa.html",
      "title": "Analyzing mass spectrometry data with limpa",
      "author": "Mengbo Li and Gordon K. Smyth",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Background",
        "How to get help",
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        "Quick start",
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        "Quantification without protein summaries",
        "Data input",
        "The detection probability curve",
        "Quantification",
        "Differential expression",
        "Working with data already summarized at the protein-level",
        "Post-translational modifications (PTMs) or immunoprecipitation mass spectrometry (IP-MS)",
        "Differential peptide usage",
        "Very large datasets",
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        "Acknowledgements",
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      "modified": "2026-04-07 03:44:14",
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