{
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  "Package": "LipidTrend",
  "Title": "LipidTrend: Analysis and Visualization of Lipid Feature\nTendencies",
  "Version": "1.3.0",
  "Authors@R": "c(\nperson(\"Wei-Chung\", \"Cheng\", email=\"chenglabomics@gmail.com\",\nrole = c(\"aut\",\"cre\",\"cph\"), comment = c(ORCID = \"0000-0002-1229-4857\")),\nperson(\"Chia-Hsin \", \"Liu\", role = c(\"aut\", \"ctb\")),\nperson(\"Pei-Chun\", \"Shen\", role = c(\"aut\", \"ctb\")),\nperson(\"Wen-Jen\", \"Lin\", role = c(\"aut\",\"ctb\")),\nperson(\"Hung-Ching\", \"Chang\", role = c(\"aut\",\"ctb\")),\nperson(\"Meng-Hsin\", \"Tsai\", role = c(\"aut\",\"ctb\"))\n)",
  "Description": "\"LipidTrend\" is an R package that implements a\npermutation-based statistical test to identify significant\ndifferences in lipidomic features between groups. The test\nincorporates Gaussian kernel smoothing of region statistics to\nimprove stability and accuracy, particularly when dealing with\nsmall sample sizes. This package also includes two plotting\nfunctions for visualizing significant tendencies in 1D and 2D\nfeature data, respectively.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/BioinfOMICS/LipidTrend",
  "BugReports": "https://github.com/BioinfOMICS/LipidTrend/issues",
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  "Config/pak/sysreqs": "zlib1g-dev",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 13:05:06 UTC",
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  "Author": "Wei-Chung Cheng [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0002-1229-4857>),\nChia-Hsin Liu [aut, ctb],\nPei-Chun Shen [aut, ctb],\nWen-Jen Lin [aut, ctb],\nHung-Ching Chang [aut, ctb],\nMeng-Hsin Tsai [aut, ctb]",
  "Maintainer": "Wei-Chung Cheng <chenglabomics@gmail.com>",
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    "show"
  ],
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      "title": "Example lipid abundance data for two-dimensional LipidTrend analysis",
      "object": "abundance_2D",
      "file": "abundance_2D.RData",
      "class": [
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        "array"
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      "object": "char_table_2D",
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        "Total.DB"
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      "class": [
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      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "lipid_se_CL",
      "title": "Example Dataset for one-dimensional data",
      "object": "lipid_se_CL",
      "file": "lipid_se_CL.RData",
      "class": [
        "SummarizedExperiment"
      ],
      "fields": [],
      "table": false,
      "tojson": false
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  "_help": [
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      "page": "abundance_2D",
      "title": "Example lipid abundance data for two-dimensional LipidTrend analysis",
      "topics": [
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      ]
    },
    {
      "page": "abundance_CL",
      "title": "Example lipid abundance data for one-dimensional LipidTrend analysis",
      "topics": [
        "abundance_CL"
      ]
    },
    {
      "page": "analyzeLipidRegion",
      "title": "Conduct statistical to analyze lipid features tendencies",
      "topics": [
        "analyzeLipidRegion"
      ]
    },
    {
      "page": "char_table_2D",
      "title": "Example lipid characteristics table for two-dimensional LipidTrend analysis",
      "topics": [
        "char_table_2D"
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    },
    {
      "page": "char_table_CL",
      "title": "Example lipid characteristics table for one-dimensional LipidTrend analysis",
      "topics": [
        "char_table_CL"
      ]
    },
    {
      "page": "even_chain_result",
      "title": "Get Even Chain Result from LipidTrendSE",
      "topics": [
        "even_chain_result",
        "even_chain_result,LipidTrendSE-method"
      ]
    },
    {
      "page": "group_info",
      "title": "Example group information table for LipidTrend analysis",
      "topics": [
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      "page": "lipid_se_2D",
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      "topics": [
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    {
      "page": "LipidTrendSE-class",
      "title": "Class for storing analyzeLipidRegion analysis results",
      "topics": [
        "LipidTrendSE-class"
      ]
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    {
      "page": "LipidTrendSE-validity",
      "title": "Validate LipidTrendSE object",
      "topics": [
        "LipidTrendSE-validity"
      ]
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      "title": "Get Odd Chain Result from LipidTrendSE",
      "topics": [
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    },
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        "plotRegion2D,LipidTrendSE-method"
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      "topics": [
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        "result,LipidTrendSE-method"
      ]
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