{
  "_id": "6a284700732311cd875843fb",
  "Package": "TiDEomics",
  "Title": "Time-course Differential Expression analysis of omics data",
  "Version": "0.99.1",
  "Date": "2026-04-29",
  "Authors@R": "person(\"Tianen\", \"He\",\nemail = \"tianen.he@ndm.ox.ac.uk\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-6864-0723\"))",
  "Description": "TiDEomics provides tools for time-course omics data\nanalysis, focusing on differential expression across multiple\nexperimental groups (>2 conditions). The package implements\nworkflows for quality control, data processing, and analysis of\ntemporal patterns, enabling integrated analysis of all groups\nin addition to pairwise comparisons. It supports datasets with\nmissing values, including mass spectrometry-based proteomics,\nand operates on SummarizedExperiment objects to ensure\ncompatibility with the Bioconductor ecosystem.",
  "License": "GPL (>= 2)",
  "URL": "https://github.com/hte123/TiDEomics,\nhttps://hte123.github.io/TiDEomics",
  "BugReports": "https://github.com/hte123/TiDEomics/issues",
  "biocViews": "Software, GeneExpression, DifferentialExpression,\nProteomics, Transcriptomics, TimeCourse, MultipleComparison,\nPathways, Visualization, MassSpectrometry, QualityControl",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "LazyData": "false",
  "VignetteBuilder": "knitr",
  "Config/testthat/edition": "3",
  "Config/roxygen2/version": "8.0.0",
  "Config/pak/sysreqs": "libcairo2-dev cmake libfontconfig1-dev\nlibfreetype6-dev libglpk-dev make libicu-dev libpng-dev\nlibuv1-dev libxml2-dev libssl-dev perl python3 zlib1g-dev",
  "Repository": "https://biocstaging.r-universe.dev",
  "Date/Publication": "2026-06-09 15:29:10 UTC",
  "RemoteUrl": "https://github.com/BiocStaging/TiDEomics",
  "RemoteRef": "HEAD",
  "RemoteSha": "6f1fffe160a525a5c392986bcce127b6e74cf5a2",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-09 16:41:17 UTC",
    "User": "root"
  },
  "Author": "Tianen He [aut, cre] (ORCID: <https://orcid.org/0000-0001-6864-0723>)",
  "Maintainer": "Tianen He <tianen.he@ndm.ox.ac.uk>",
  "MD5sum": "4f663432fee6855e273762a89040ad48",
  "_user": "biocstaging",
  "_type": "src",
  "_file": "TiDEomics_0.99.1.tar.gz",
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  "_filesize": 3999397,
  "_sha256": "35f2b2a611b2d6218d3f138c70a08693aefc20eb3935b1ef1b8ce54446ba2100",
  "_created": "2026-06-09T16:41:17.000Z",
  "_published": "2026-06-09T17:01:52.460Z",
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  "_bioccheck": {
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    "warning": 0,
    "note": 6
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  "_buildurl": "https://github.com/r-universe/biocstaging/actions/runs/27220764490",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/BiocStaging/TiDEomics",
  "_commit": {
    "id": "6f1fffe160a525a5c392986bcce127b6e74cf5a2",
    "author": "Tianen He <tianen.he@ndm.ox.ac.uk>",
    "committer": "Tianen He <tianen.he@ndm.ox.ac.uk>",
    "message": "Update formatting\n\nAdd biocViews (MassSpectrometry, QualityControl) in DESCRIPTION. Fixed indentation in R/prepare_WGCNA.R. Split long lines and corrected WGCNA background in vignettes/TiDEomics.Rmd. Bump package Version to 0.99.1.\n",
    "time": 1781018950
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  "_maintainer": {
    "name": "Tianen He",
    "email": "tianen.he@ndm.ox.ac.uk",
    "login": "hte123",
    "description": "",
    "uuid": 59926992,
    "orcid": "0000-0001-6864-0723"
  },
  "_distro": "noble",
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 4.5.0",
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      "package": "ComplexHeatmap",
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      "package": "ggforce",
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      "package": "ggplot2",
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      "package": "methods",
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      "package": "randtests",
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    {
      "package": "SummarizedExperiment",
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    {
      "package": "tidyr",
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      "package": "WGCNA",
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      "package": "DT",
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  "_owner": "biocstaging",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
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      "week": "2026-18",
      "n": 9
    },
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      "week": "2026-19",
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  ],
  "_tags": [],
  "_topics": [
    "software",
    "geneexpression",
    "differentialexpression",
    "proteomics",
    "transcriptomics",
    "timecourse",
    "multiplecomparison",
    "pathways",
    "visualization",
    "massspectrometry",
    "qualitycontrol"
  ],
  "_stars": 0,
  "_contributors": [
    {
      "user": "hte123",
      "count": 22,
      "uuid": 59926992
    }
  ],
  "_userbio": {
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    "type": "organization",
    "name": "BiocStaging"
  },
  "_downloads": {
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/TiDEomics"
  },
  "_devurl": "https://github.com/hte123/tideomics",
  "_pkgdown": "https://hte123.github.io/TiDEomics",
  "_searchresults": 2,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "extra/TiDEomics.html",
    "manual.pdf"
  ],
  "_cranurl": false,
  "_exports": [
    "calc_feature_property",
    "calc_mean_sd",
    "create_input",
    "DE_between_group",
    "DE_between_time",
    "decomp_variance",
    "enrichGO_list",
    "enrichGO_rank",
    "enrichR_list",
    "extract_segment_trends",
    "get_custom_palette",
    "group_specific_features",
    "impute_groups",
    "merge_groups",
    "merge_replicates",
    "normalise_to_start",
    "plot_breakpoints",
    "plot_cor_matrix",
    "plot_cv",
    "plot_DE_between_time",
    "plot_distribution",
    "plot_GO",
    "plot_ID",
    "plot_missing",
    "plot_modules_h",
    "plot_modules_v",
    "plot_pca",
    "plot_pca_3D",
    "plot_pca_arrows",
    "plot_pca_by_group",
    "plot_segments",
    "plot_trend",
    "plot_umap",
    "plot_umap_by_group",
    "plot_variance",
    "plot_volcano",
    "plot_WGCNA",
    "prepare_WGCNA",
    "run_Trendy",
    "run_WGCNA",
    "set_custom_palette",
    "split_groups",
    "summarise_feature_property",
    "summarise_module_pattern",
    "summarise_Trendy",
    "theme_custom",
    "WGCNA_module"
  ],
  "_datasets": [
    {
      "name": "example_net",
      "title": "'run_WGCNA()' output object for runnable examples",
      "object": "example_net",
      "file": "example_net.rda",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "example_obj",
      "title": "SummarizedExperiment object for runnable examples",
      "object": "example",
      "file": "example.rda",
      "class": [
        "SummarizedExperiment"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "example_res_list",
      "title": "'run_Trendy' output object for runnable examples",
      "object": "example_res_list",
      "file": "example_res_list.rda",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "tutorial_data",
      "title": "Dataset for TiDEomics tutorial, expression matrix",
      "object": "tutorial_data",
      "file": "tutorial_data.rda",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Feature",
        "RNA_untreated_0h_R1_1",
        "RNA_untreated_24h_R1_2",
        "RNA_IFNbeta_2h_R1_1",
        "RNA_IFNbeta_24h_R1_2",
        "RNA_IFNbeta_4h_R1_1",
        "RNA_IFNbeta_6h_R1_1",
        "RNA_IFNbeta_8h_R1_2",
        "RNA_IFNgamma_2h_R1_1",
        "RNA_IFNgamma_24h_R1_2",
        "RNA_IFNgamma_4h_R1_1",
        "RNA_IFNgamma_6h_R1_1",
        "RNA_IFNgamma_8h_R1_2",
        "RNA_LPS_2h_R1_1",
        "RNA_LPS_4h_R1_1",
        "RNA_LPS_6h_R1_1",
        "RNA_LPS_8h_R1_2",
        "RNA_untreated_0h_R2_1",
        "RNA_untreated_24h_R2_2",
        "RNA_untreated_8h_R2_2",
        "RNA_IFNbeta_2h_R2_1",
        "RNA_IFNbeta_24h_R2_2",
        "RNA_IFNbeta_4h_R2_1",
        "RNA_IFNbeta_6h_R2_1",
        "RNA_IFNbeta_8h_R2_2",
        "RNA_IFNgamma_2h_R2_1",
        "RNA_IFNgamma_24h_R2_2",
        "RNA_IFNgamma_4h_R2_1",
        "RNA_IFNgamma_6h_R2_1",
        "RNA_IFNgamma_8h_R2_2",
        "RNA_LPS_2h_R2_1",
        "RNA_LPS_24h_R2_2",
        "RNA_LPS_4h_R2_1",
        "RNA_LPS_6h_R2_1",
        "RNA_LPS_8h_R2_2",
        "RNA_IFNbeta_0h_R1_1",
        "RNA_IFNbeta_0h_R2_1",
        "RNA_IFNgamma_0h_R1_1",
        "RNA_IFNgamma_0h_R2_1",
        "RNA_LPS_0h_R1_1",
        "RNA_LPS_0h_R2_1"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
    {
      "name": "tutorial_sample_info",
      "title": "Dataset for TiDEomics tutorial, sample information",
      "object": "tutorial_sample_info",
      "file": "tutorial_sample_info.rda",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Sample",
        "Group",
        "Time",
        "Replicate",
        "Batch"
      ],
      "rows": 40,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "calc_feature_property",
      "title": "Calculate feature property",
      "topics": [
        "calc_feature_property"
      ]
    },
    {
      "page": "calc_mean_sd",
      "title": "Calculate mean and SD",
      "topics": [
        "calc_mean_sd"
      ]
    },
    {
      "page": "create_input",
      "title": "Create object",
      "topics": [
        "create_input"
      ]
    },
    {
      "page": "DE_between_group",
      "title": "DE between groups",
      "topics": [
        "DE_between_group"
      ]
    },
    {
      "page": "DE_between_time",
      "title": "DE between time points",
      "topics": [
        "DE_between_time"
      ]
    },
    {
      "page": "decomp_variance",
      "title": "Variance decomposition",
      "topics": [
        "decomp_variance"
      ]
    },
    {
      "page": "enrichGO_list",
      "title": "GO enrichment with gene sets",
      "topics": [
        "enrichGO_list"
      ]
    },
    {
      "page": "enrichGO_rank",
      "title": "GO enrichment with ranked gene list",
      "topics": [
        "enrichGO_rank"
      ]
    },
    {
      "page": "enrichR_list",
      "title": "Gene-set enrichment via enrichR",
      "topics": [
        "enrichR_list"
      ]
    },
    {
      "page": "example_net",
      "title": "'run_WGCNA()' output object for runnable examples",
      "topics": [
        "example_net"
      ]
    },
    {
      "page": "example_obj",
      "title": "SummarizedExperiment object for runnable examples",
      "topics": [
        "example_obj"
      ]
    },
    {
      "page": "example_res_list",
      "title": "'run_Trendy' output object for runnable examples",
      "topics": [
        "example_res_list"
      ]
    },
    {
      "page": "extract_segment_trends",
      "title": "Extract feature trends",
      "topics": [
        "extract_segment_trends"
      ]
    },
    {
      "page": "get_custom_palette",
      "title": "Get custom color palette",
      "topics": [
        "get_custom_palette"
      ]
    },
    {
      "page": "group_specific_features",
      "title": "Group specific features",
      "topics": [
        "group_specific_features"
      ]
    },
    {
      "page": "impute_groups",
      "title": "Impute missing values",
      "topics": [
        "impute_groups"
      ]
    },
    {
      "page": "merge_groups",
      "title": "Merge groups into one object",
      "topics": [
        "merge_groups"
      ]
    },
    {
      "page": "merge_replicates",
      "title": "Merge replicates",
      "topics": [
        "merge_replicates"
      ]
    },
    {
      "page": "normalise_to_start",
      "title": "Normalise to time 0",
      "topics": [
        "normalise_to_start"
      ]
    },
    {
      "page": "plot_breakpoints",
      "title": "Plot breakpoint distribution",
      "topics": [
        "plot_breakpoints"
      ]
    },
    {
      "page": "plot_cor_matrix",
      "title": "Plot correlation matrix",
      "topics": [
        "plot_cor_matrix"
      ]
    },
    {
      "page": "plot_cv",
      "title": "Plot coefficient of variation (CV)",
      "topics": [
        "plot_cv"
      ]
    },
    {
      "page": "plot_DE_between_time",
      "title": "DE number between time points",
      "topics": [
        "plot_DE_between_time"
      ]
    },
    {
      "page": "plot_distribution",
      "title": "Abundance distribution plot",
      "topics": [
        "plot_distribution"
      ]
    },
    {
      "page": "plot_GO",
      "title": "Plot GO enrichment",
      "topics": [
        "plot_GO"
      ]
    },
    {
      "page": "plot_ID",
      "title": "Plot number of identified features",
      "topics": [
        "plot_ID"
      ]
    },
    {
      "page": "plot_missing",
      "title": "Plot missing rate",
      "topics": [
        "plot_missing"
      ]
    },
    {
      "page": "plot_modules_h",
      "title": "Plot modules (horizontal layout)",
      "topics": [
        "plot_modules_h"
      ]
    },
    {
      "page": "plot_modules_v",
      "title": "Plot modules (vertical layout)",
      "topics": [
        "plot_modules_v"
      ]
    },
    {
      "page": "plot_pca",
      "title": "Plot PCA",
      "topics": [
        "plot_pca"
      ]
    },
    {
      "page": "plot_pca_3D",
      "title": "Plot PCA in 3D",
      "topics": [
        "plot_pca_3D"
      ]
    },
    {
      "page": "plot_pca_arrows",
      "title": "Plot PCA with arrows",
      "topics": [
        "plot_pca_arrows"
      ]
    },
    {
      "page": "plot_pca_by_group",
      "title": "Plot PCA by group",
      "topics": [
        "plot_pca_by_group"
      ]
    },
    {
      "page": "plot_segments",
      "title": "Plot segmented regression",
      "topics": [
        "plot_segments"
      ]
    },
    {
      "page": "plot_trend",
      "title": "Plot feature abundance over time",
      "topics": [
        "plot_trend"
      ]
    },
    {
      "page": "plot_umap",
      "title": "Plot UMAP",
      "topics": [
        "plot_umap"
      ]
    },
    {
      "page": "plot_umap_by_group",
      "title": "Plot UMAP by group",
      "topics": [
        "plot_umap_by_group"
      ]
    },
    {
      "page": "plot_variance",
      "title": "Plot variance decomposition",
      "topics": [
        "plot_variance"
      ]
    },
    {
      "page": "plot_volcano",
      "title": "Volcano plot of DE results",
      "topics": [
        "plot_volcano"
      ]
    },
    {
      "page": "plot_WGCNA",
      "title": "Plot WGCNA results",
      "topics": [
        "plot_WGCNA"
      ]
    },
    {
      "page": "prepare_WGCNA",
      "title": "Prepare data and choose power for WGCNA",
      "topics": [
        "prepare_WGCNA"
      ]
    },
    {
      "page": "run_Trendy",
      "title": "Segmented regression analysis",
      "topics": [
        "run_Trendy"
      ]
    },
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