{
  "_id": "6a1aeb601d7bb097a09f3d81",
  "Package": "lipidr",
  "Title": "Data Mining and Analysis of Lipidomics Datasets",
  "Version": "2.27.0",
  "Authors@R": "c(\nperson(\n\"Ahmed\", \"Mohamed\",\nemail = \"mohamed@kuicr.kyoto-u.ac.jp\", role = \"cre\",\ncomment = c(ORCID = \"0000-0001-6507-5300\")\n),\nperson(\n\"Ahmed\", \"Mohamed\",\nemail = \"ahmed.mohamed@qimrberghofer.edu.au\", role = \"aut\"\n),\nperson(\n\"Jeffrey\", \"Molendijk\",\nemail = \"Jeffrey.Molendijk@qimrberghofer.edu.au\", role = \"aut\"\n))",
  "Description": "lipidr an easy-to-use R package implementing a complete\nworkflow for downstream analysis of targeted and untargeted\nlipidomics data. lipidomics results can be imported into lipidr\nas a numerical matrix or a Skyline export, allowing integration\ninto current analysis frameworks. Data mining of lipidomics\ndatasets is enabled through integration with Metabolomics\nWorkbench API. lipidr allows data inspection, normalization,\nunivariate and multivariate analysis, displaying informative\nvisualizations. lipidr also implements a novel Lipid Set\nEnrichment Analysis (LSEA), harnessing molecular information\nsuch as lipid class, total chain length and unsaturation.",
  "License": "MIT + file LICENSE",
  "VignetteBuilder": "knitr",
  "biocViews": "Lipidomics, MassSpectrometry, Normalization, QualityControl,\nVisualization",
  "Language": "en-US",
  "RoxygenNote": "7.2.3",
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  "URL": "https://github.com/ahmohamed/lipidr",
  "BugReports": "https://github.com/ahmohamed/lipidr/issues/",
  "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libssl-dev\nzlib1g-dev",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:50:06 UTC",
  "RemoteUrl": "https://github.com/bioc/lipidr",
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  "NeedsCompilation": "no",
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    "Date": "2026-05-30 09:39:37 UTC",
    "User": "root"
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  "Author": "Ahmed Mohamed [cre] (ORCID: <https://orcid.org/0000-0001-6507-5300>),\nAhmed Mohamed [aut],\nJeffrey Molendijk [aut]",
  "Maintainer": "Ahmed Mohamed <mohamed@kuicr.kyoto-u.ac.jp>",
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    "de_design",
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    "plot_chain_distribution",
    "plot_class_enrichment",
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    "plot_mva",
    "plot_mva_loadings",
    "plot_results_volcano",
    "plot_samples",
    "plot_trend",
    "read_mw_datamatrix",
    "read_mwTab",
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    "remove_non_parsed_molecules",
    "set_logged",
    "set_normalized",
    "set_summarized",
    "significant_lipidsets",
    "significant_molecules",
    "summarize_transitions",
    "top_lipids",
    "update_molecule_names",
    "use_interactive_graphics"
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      "title": "Example dataset (normalized and log2 transformed)",
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      "file": "data_normalized.rda",
      "class": [
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      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
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      "title": "Default values for lipidr internal functions A set of default mappings and annotation used internally to correctly parse lipid molecule names.",
      "object": "lipidDefaults",
      "file": "lipidDefaults.rda",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
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      "title": "Patterns used in parsing lipid names",
      "object": "lipidnames_pattern",
      "file": "lipidnames_pattern.rda",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
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  "_help": [
    {
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      "title": "Add sample annotation to Skyline data frame",
      "topics": [
        "add_sample_annotation"
      ]
    },
    {
      "page": "annotate_lipids",
      "title": "Parse molecule names to extract lipid class and chain information.",
      "topics": [
        "annotate_lipids"
      ]
    },
    {
      "page": "as_lipidomics_experiment",
      "title": "Convert data.frame/matrix to LipidomicsExperiment",
      "topics": [
        "as_lipidomics_experiment"
      ]
    },
    {
      "page": "de_analysis",
      "title": "Differential analysis of lipids between sample groups",
      "topics": [
        "de_analysis",
        "de_design",
        "plot_results_volcano",
        "significant_molecules"
      ]
    },
    {
      "page": "filter_by_cv",
      "title": "Remove molecules with CV larger that a threshold",
      "topics": [
        "filter_by_cv"
      ]
    },
    {
      "page": "gen_lipidsets",
      "title": "Generate lipid sets from lipid molecule names",
      "topics": [
        "gen_lipidsets"
      ]
    },
    {
      "page": "impute_na",
      "title": "Impute missing values in a LipidomicsExperiment",
      "topics": [
        "impute_na"
      ]
    },
    {
      "page": "set_attr",
      "title": "Functions to get and set attributes of LipidomicsExperiment objects",
      "topics": [
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        "is_normalized",
        "is_summarized",
        "set_logged",
        "set_normalized",
        "set_summarized"
      ]
    },
    {
      "page": "LipidomicsExperiment",
      "title": "Constructor for Lipidomics experiment from list of assays",
      "topics": [
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      ]
    },
    {
      "page": "LipidomicsExperiment-class",
      "title": "LipidomicsExperiment object",
      "topics": [
        ".LipidomicsExperiment",
        "LipidomicsExperiment-class"
      ]
    },
    {
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      "title": "Metabolomics Workbench integration",
      "topics": [
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        "list_mw_studies",
        "read_mwTab",
        "read_mw_datamatrix"
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    },
    {
      "page": "lsea",
      "title": "Lipid set enrichment analysis (LSEA)",
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        "plot_class_enrichment",
        "plot_enrichment",
        "significant_lipidsets"
      ]
    },
    {
      "page": "mva",
      "title": "Perform multivariate analyses to investigate sample clustering",
      "topics": [
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        "plot_mva",
        "plot_mva_loadings",
        "top_lipids"
      ]
    },
    {
      "page": "non_parsed_molecules",
      "title": "Get a list of molecules that couldn't be parsed by 'lipidr'",
      "topics": [
        "non_parsed_molecules"
      ]
    },
    {
      "page": "normalize_istd",
      "title": "Normalize each class by its corresponding internal standard(s).",
      "topics": [
        "normalize_istd"
      ]
    },
    {
      "page": "normalize_pqn",
      "title": "Perform Probabilistic Quotient Normalization for intensities.",
      "topics": [
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    },
    {
      "page": "plot_chain_distribution",
      "title": "Plot logFC of lipids per class showing chain information",
      "topics": [
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    },
    {
      "page": "plot_lipidclass",
      "title": "Informative plots to investigate lipid classes",
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      ]
    },
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      "title": "Informative plots to investigate individual lipid molecules",
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      "title": "Informative plots to investigate samples",
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      "title": "Rename molecules in a dataset.",
      "topics": [
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      ]
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      "source": "workflow.Rmd",
      "filename": "workflow.html",
      "title": "Workflow",
      "author": "Ahmed Mohamed",
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      "headings": [
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        "Differential analysis",
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