{
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  "Package": "MetPhenoR",
  "Title": "A Transparent Analysis Pipeline for Mammalian Metabolic\nPhenotype Microarray Data",
  "Version": "1.3",
  "Authors@R": "c(person(given=\"Katja\",family= \"Danielzik\", email=\"katja.danielzik@uni-due.de\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment=c(ORCID=\"0009-0007-5021-6212\")),\nperson(given=\"Willson\",family = \"Tjioe\",\nrole = \"aut\",\ncomment=c(ORCID=\"0009-0003-3530-1727\")),\nperson(given=\"Julia\", family=\"Asche\",\nrole = \"ctb\"),\nperson(given=\"Johann\",family=\"Matschke\",\nrole=\"ctb\",\ncomment=c(ORCID=\"0000-0003-4878-8741\")),\nperson(given=\"Daniel\",family=\"Hoffmann\",\nrole=\"ctb\",\ncomment=c(ORCID=\"0000-0003-2973-7869\")))",
  "Description": "Provides a transparent, end-to-end workflow for analyzing\nhigh-throughput phenotype microarray data in mammalian cell\ncultures. It begins with automated reading and noise\ncorrection, followed by comprehensive quality control via\nvisual diagnostics, i.e. detecting missing wells, anomalous\ncurve shapes and variance. Area under Curve is computed as a\nsummary metric. Biological annotations (custom or in-built for\nPM-M01,PM-M02, PM-M11 - PM-M14) enable group-level comparisons.",
  "License": "GPL (>= 3)",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "Config/testthat/edition": "3",
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  "VignetteBuilder": "knitr",
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  "URL": "https://github.com/KatjaDanielzik/MetPhenoR",
  "BugReports": "https://github.com/KatjaDanielzik/MetPhenoR/issues",
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  "Repository": "https://katjadanielzik.r-universe.dev",
  "Date/Publication": "2026-11-12 08:17:30 UTC",
  "RemoteUrl": "https://github.com/katjadanielzik/metphenor",
  "RemoteRef": "HEAD",
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  "NeedsCompilation": "no",
  "Packaged": {
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    "User": "root"
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  "Author": "Katja Danielzik [aut, cre, cph] (ORCID:\n<https://orcid.org/0009-0007-5021-6212>),\nWillson Tjioe [aut] (ORCID: <https://orcid.org/0009-0003-3530-1727>),\nJulia Asche [ctb],\nJohann Matschke [ctb] (ORCID: <https://orcid.org/0000-0003-4878-8741>),\nDaniel Hoffmann [ctb] (ORCID: <https://orcid.org/0000-0003-2973-7869>)",
  "Maintainer": "Katja Danielzik <katja.danielzik@uni-due.de>",
  "_user": "katjadanielzik",
  "_type": "src",
  "_file": "MetPhenoR_1.3.tar.gz",
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  "_filesize": 10099665,
  "_sha256": "ca9d4ba03be7b5fd70e8bbcebd61474120c5af713cf640cebb5ef813598b8fa3",
  "_expires": "2027-02-20T15:21:32.000Z",
  "_created": "2026-11-12T14:57:38.000Z",
  "_published": "2026-11-12T15:21:35.145Z",
  "_upstream": "https://github.com/katjadanielzik/metphenor",
  "_status": "success",
  "_maintainer": {
    "name": "Katja Danielzik",
    "email": "katja.danielzik@uni-due.de",
    "login": "katjadanielzik",
    "description": "",
    "uuid": 161830853,
    "orcid": "0009-0007-5021-6212"
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    "message": "updated NEWS\n",
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  "_tags": [],
  "_topics": [
    "high-throughput",
    "mammalian",
    "metabolism",
    "microarray",
    "odin",
    "phenotyping"
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    "annotate_chemical",
    "annotate_metadata",
    "classify_growth_curve_types",
    "compute_auc_ci",
    "compute_auc_ratio",
    "filter_data",
    "plot_auc",
    "plot_auc_ratio_by_group",
    "plot_auc_ratio_heatmap",
    "plot_auc_ratio_violin",
    "plot_controls_tween_all_plate",
    "plot_controls_tween_per_plate",
    "plot_growth_curve",
    "plot_latest_timepoint",
    "qc_data",
    "read_folder"
  ],
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    {
      "name": "PlateInfo",
      "title": "An example '..._PlateInfo.csv\" file",
      "object": "PlateInfo",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "PlateId",
        "Project Name",
        "Project Code",
        "Plate Type",
        "Sample",
        "Loaded At",
        "Incubation Hours",
        "Incubation Temperature Celsius",
        "Incubated Offline",
        "Cycle Time Minutes",
        "Position",
        "Protocol",
        "Description"
      ],
      "rows": 8,
      "table": true,
      "tojson": true
    },
    {
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      "title": "Annotations for metabolic plates PM-M01 and PM-M02",
      "object": "PM_M01_M02",
      "class": [
        "spec_tbl_df",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Plate.Type",
        "Well",
        "Chemical",
        "Kegg Link",
        "Info",
        "KEGG",
        "module_id",
        "module_name",
        "upper_hierarchy",
        "middle_hierarchy",
        "lower_hierarchy"
      ],
      "rows": 422,
      "table": true,
      "tojson": true
    },
    {
      "name": "PM_M11_M14",
      "title": "Annotations for anti-cancer drug plates PM-M11 to PM-M14",
      "object": "PM_M11_M14",
      "class": [
        "spec_tbl_df",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Plate.Type",
        "Well",
        "Chemical",
        "Info",
        "KEGG",
        "CAS",
        "Inhibition Target",
        "Mechanism of Action",
        "Affected Pathway",
        "Used to Treat",
        "Clinical Status (March 2025)"
      ],
      "rows": 384,
      "table": true,
      "tojson": true
    },
    {
      "name": "processed_data",
      "title": "Example data set as result of read_folder.R with sample_column = \"Sample\" and variables = c(\"cell.line\", \"LKB1.status\", \"radiation.dose\")",
      "object": "processed_data",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "RawRead",
      "title": "Example Raw Read from Odin Biolog",
      "object": "RawRead",
      "class": [
        "spec_tbl_df",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Id",
        "PlateId",
        "Wavelength",
        "Actual Temperature Celsius",
        "Target Temperature Celsius",
        "Read At",
        "A01",
        "A02",
        "A03",
        "A04",
        "A05",
        "A06",
        "A07",
        "A08",
        "A09",
        "A10",
        "A11",
        "A12",
        "B01",
        "B02",
        "B03",
        "B04",
        "B05",
        "B06",
        "B07",
        "B08",
        "B09",
        "B10",
        "B11",
        "B12",
        "C01",
        "C02",
        "C03",
        "C04",
        "C05",
        "C06",
        "C07",
        "C08",
        "C09",
        "C10",
        "C11",
        "C12",
        "D01",
        "D02",
        "D03",
        "D04",
        "D05",
        "D06",
        "D07",
        "D08",
        "D09",
        "D10",
        "D11",
        "D12",
        "E01",
        "E02",
        "E03",
        "E04",
        "E05",
        "E06",
        "E07",
        "E08",
        "E09",
        "E10",
        "E11",
        "E12",
        "F01",
        "F02",
        "F03",
        "F04",
        "F05",
        "F06",
        "F07",
        "F08",
        "F09",
        "F10",
        "F11",
        "F12",
        "G01",
        "G02",
        "G03",
        "G04",
        "G05",
        "G06",
        "G07",
        "G08",
        "G09",
        "G10",
        "G11",
        "G12",
        "H01",
        "H02",
        "H03",
        "H04",
        "H05",
        "H06",
        "H07",
        "H08",
        "H09",
        "H10",
        "H11",
        "H12"
      ],
      "rows": 286,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "annotate_chemical",
      "title": "Annotate assay data with chemical identities",
      "topics": [
        "annotate_chemical"
      ]
    },
    {
      "page": "annotate_metadata",
      "title": "Annotate assay data with metadata",
      "topics": [
        "annotate_metadata"
      ]
    },
    {
      "page": "classify_growth_curve_types",
      "title": "Classify Growth Curve Dynamics",
      "topics": [
        "classify_growth_curve_types"
      ]
    },
    {
      "page": "compute_auc_ci",
      "title": "Estimate Area Under the Curve (AUC) with Bootstrap Confidence Intervals",
      "topics": [
        "compute_auc_ci"
      ]
    },
    {
      "page": "compute_auc_ratio",
      "title": "Compute AUC Ratio Relative to Controls",
      "topics": [
        "compute_auc_ratio"
      ]
    },
    {
      "page": "filter_data",
      "title": "Exclude 96-well plate",
      "topics": [
        "filter_data"
      ]
    },
    {
      "page": "PlateInfo",
      "title": "An example '..._PlateInfo.csv\" file",
      "topics": [
        "PlateInfo"
      ]
    },
    {
      "page": "plot_auc",
      "title": "Plot AUC Profiles by Plate and Experimental Conditions",
      "topics": [
        "plot_auc"
      ]
    },
    {
      "page": "plot_auc_ratio_by_group",
      "title": "Plot AUC ratio heatmap by group",
      "topics": [
        "plot_auc_ratio_by_group"
      ]
    },
    {
      "page": "plot_auc_ratio_heatmap",
      "title": "Plot AUC ratio heatmap",
      "topics": [
        "plot_auc_ratio_heatmap"
      ]
    },
    {
      "page": "plot_auc_ratio_violin",
      "title": "Plot AUC ratio distribution as violin plots",
      "topics": [
        "plot_auc_ratio_violin"
      ]
    },
    {
      "page": "plot_controls_tween_all_plate",
      "title": "Plot Controls vs Tween Across All Plates (with Control Reference Range)",
      "topics": [
        "plot_controls_tween_all_plate"
      ]
    },
    {
      "page": "plot_controls_tween_per_plate",
      "title": "AUC Plot for Controls and Tween Compounds within plate",
      "topics": [
        "plot_controls_tween_per_plate"
      ]
    },
    {
      "page": "plot_growth_curve",
      "title": "Visualize Growth Curves and Plate Layouts from Classified Data",
      "topics": [
        "plot_growth_curve"
      ]
    },
    {
      "page": "plot_latest_timepoint",
      "title": "Plot Final Time Point per Experimental Condition",
      "topics": [
        "plot_latest_timepoint"
      ]
    },
    {
      "page": "PM_M01_M02",
      "title": "Annotations for metabolic plates PM-M01 and PM-M02",
      "topics": [
        "PM_M01_M02"
      ]
    },
    {
      "page": "PM_M11_M14",
      "title": "Annotations for anti-cancer drug plates PM-M11 to PM-M14",
      "topics": [
        "PM_M11_M14"
      ]
    },
    {
      "page": "processed_data",
      "title": "Example data set as result of read_folder.R with sample_column = \"Sample\" and variables = c(\"cell.line\", \"LKB1.status\", \"radiation.dose\")",
      "topics": [
        "processed_data"
      ]
    },
    {
      "page": "qc_data",
      "title": "Quality Control for input data after noise correction",
      "topics": [
        "qc_data"
      ]
    },
    {
      "page": "RawRead",
      "title": "Example Raw Read from Odin Biolog",
      "topics": [
        "RawRead"
      ]
    },
    {
      "page": "read_folder",
      "title": "Process CSV Plate Data stored in folder into data frame in long format",
      "topics": [
        "read_folder"
      ]
    }
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      "filename": "MetPheno.html",
      "title": "MetPhenoR",
      "author": "Katja Danielzik (katja.danielzik@uni-due.de)",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Aim of this package",
        "Important to Know Before You Start",
        "Workflow",
        "Step 1: Prepare your Data",
        "Step 2: Read your Data with read_folder() function",
        "Step3: Check your data with qc_data() function",
        "Step 4 (Optional): Visualize the Final Timepoint: plot_latest_timepoint()",
        "Step 5: Annotate Chemicals to PlateType and Well with annotate_chemical()",
        "Custom annotation files",
        "Step 6: Quality control of OD curves",
        "Step 7: Summarize curves to Area under Curve (AUC)",
        "Step 9: Check Control Well Variability",
        "Step 10: Compare AUCs Per Plate",
        "Step 11: Normalize AUC to AUC ratios and visualize",
        "Step 12: Annotation of metadata",
        "Step 13: Visualiation of AUC Ratios by group"
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      "modified": "2026-10-26 14:49:59",
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