{
  "_id": "6a1acda61d7bb097a09df50c",
  "Package": "GOexpress",
  "Title": "Visualise microarray and RNAseq data using gene ontology\nannotations",
  "Version": "1.47.0",
  "Date": "2025-09-03",
  "Authors@R": "c(\nperson(given=\"Kevin\", family=\"Rue-Albrecht\",\nrole = c(\"aut\", \"cre\"), email = \"kevinrue67@gmail.com\"),\nperson(give=c(\"Tharvesh\", \"M.L.\"), family=\"Ali\", role = c(\"ctb\")),\nperson(given=c(\"Paul\", \"A.\"), family=\"McGettigan\", role = c(\"ctb\")),\nperson(given=\"Belinda\", family=\"Hernandez\", role = c(\"ctb\")),\nperson(given=\"David A.\", family=\"Magee\", role = c(\"ctb\")),\nperson(given=\"Nicolas C.\", family=\"Nalpas\", role = c(\"ctb\")),\nperson(given=\"Andrew\", family=\"Parnell\", role = c(\"ctb\")),\nperson(given=c(\"Stephen\", \"V.\"), family=\"Gordon\", role = c(\"ths\")),\nperson(given=c(\"David\", \"E.\"), family=\"MacHugh\", role = c(\"ths\")),\nperson(given=\"Hugo\", family=\"Gruson\", role = c(\"ctb\")))",
  "Description": "The package contains methods to visualise the expression\nprofile of genes from a microarray or RNA-seq experiment, and\noffers a supervised clustering approach to identify GO terms\ncontaining genes with expression levels that best classify two\nor more predefined groups of samples. Annotations for the genes\npresent in the expression dataset may be obtained from Ensembl\nthrough the biomaRt package, if not provided by the user. The\ndefault random forest framework is used to evaluate the\ncapacity of each gene to cluster samples according to the\nfactor of interest. Finally, GO terms are scored by averaging\nthe rank (alternatively, score) of their respective gene sets\nto cluster the samples. P-values may be computed to assess the\nsignificance of GO term ranking. Visualisation function include\ngene expression profile, gene ontology-based heatmaps, and\nhierarchical clustering of experimental samples using gene\nexpression data.",
  "License": "GPL (>= 3)",
  "biocViews": "Software, GeneExpression, Transcription,\nDifferentialExpression, GeneSetEnrichment, DataRepresentation,\nClustering, TimeCourse, Microarray, Sequencing, RNASeq,\nAnnotation, MultipleComparison, Pathways, GO, Visualization,\nImmunoOncology",
  "URL": "https://github.com/kevinrue/GOexpress",
  "LazyData": "true",
  "Config/pak/sysreqs": "make libicu-dev libpng-dev libxml2-dev libssl-dev\nzlib1g-dev",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:39:46 UTC",
  "RemoteUrl": "https://github.com/bioc/GOexpress",
  "RemoteRef": "HEAD",
  "RemoteSha": "7e872b08cdb2dd3051e10e39f5380d74229a94de",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-30 08:09:46 UTC",
    "User": "root"
  },
  "Author": "Kevin Rue-Albrecht [aut, cre],\nTharvesh M.L. Ali [ctb],\nPaul A. McGettigan [ctb],\nBelinda Hernandez [ctb],\nDavid A. Magee [ctb],\nNicolas C. Nalpas [ctb],\nAndrew Parnell [ctb],\nStephen V. Gordon [ths],\nDavid E. MacHugh [ths],\nHugo Gruson [ctb]",
  "Maintainer": "Kevin Rue-Albrecht <kevinrue67@gmail.com>",
  "MD5sum": "77b00afce924c85525b65d482c233ade",
  "_user": "bioc",
  "_type": "src",
  "_file": "GOexpress_1.47.0.tar.gz",
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  "_filesize": 2686340,
  "_sha256": "5fe15549be2f10c7e251793e215ff761bac483f3566d8a2dcf731abb6c288729",
  "_created": "2026-05-30T08:09:46.000Z",
  "_published": "2026-05-30T11:44:38.354Z",
  "_jobs": [
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    "login": "kevinrue",
    "mastodon": "@kevinrue@fosstodon.org",
    "description": "Ingénieur diplômé;\nComputational Biologist; \nSoftware engineer;\nBioconductor contributor",
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  "_updates": [
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    "geneexpression",
    "transcription",
    "differentialexpression",
    "genesetenrichment",
    "datarepresentation",
    "clustering",
    "timecourse",
    "microarray",
    "sequencing",
    "rnaseq",
    "annotation",
    "multiplecomparison",
    "pathways",
    "go",
    "visualization",
    "immunooncology",
    "bioconductor",
    "bioconductor-package",
    "bioconductor-stats",
    "geneontology",
    "geneset-enrichment"
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  "_contributors": [
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    "name": "Bioconductor",
    "description": "Software for the analysis and comprehension of high-throughput genomic data"
  },
  "_downloads": {
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    "source": "https://www.bioconductor.org/packages/stats/bioc/GOexpress"
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  "_devurl": "https://github.com/kevinrue/goexpress",
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    "extra/citation.html",
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    "manual.pdf"
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  "_homeurl": "https://github.com/kevinrue/goexpress",
  "_realowner": "bioc",
  "_cranurl": false,
  "_exports": [
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    "expression_plot",
    "expression_plot_symbol",
    "expression_profiles",
    "expression_profiles_symbol",
    "GO_analyse",
    "heatmap_GO",
    "hist_scores",
    "list_genes",
    "plot_design",
    "pValue_GO",
    "quantiles_scores",
    "rerank",
    "subEset",
    "subset_scores",
    "table_genes"
  ],
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      "title": "Sample data from a RNAseq experiment.",
      "object": "AlvMac",
      "class": [
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      ],
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      "table": false,
      "tojson": false
    },
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        "description"
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      ],
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        "name_1006",
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      ],
      "rows": 13302,
      "table": true,
      "tojson": true
    },
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        "go_id"
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      "table": true,
      "tojson": true
    },
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      "object": "AlvMac_results",
      "class": [
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      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
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      "title": "Sample output from the 'pValue_GO()' function on an RNAseq experiment.",
      "object": "AlvMac_results.pVal",
      "class": [
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      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
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      "name": "microarray2dataset",
      "title": "Table mapping probeset identifier prefixes to datasets in the Ensembl BioMart.",
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        "microarray",
        "sample",
        "species",
        "pattern",
        "unique"
      ],
      "rows": 158,
      "table": true,
      "tojson": true
    },
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      "title": "Table mapping Ensembl gene identifier prefixes to BioMart datasets.",
      "object": "prefix2dataset",
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        "species",
        "prefix",
        "sample"
      ],
      "rows": 69,
      "table": true,
      "tojson": true
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  "_help": [
    {
      "page": "GOexpress-package",
      "title": "Visualise microarray and RNAseq data with gene ontology annotations.",
      "topics": [
        "GOexpress-package",
        "GOexpress"
      ]
    },
    {
      "page": "AlvMac",
      "title": "Sample data from a RNAseq experiment.",
      "topics": [
        "AlvMac"
      ]
    },
    {
      "page": "AlvMac_allgenes",
      "title": "Example of custom gene feature annotations.",
      "topics": [
        "AlvMac_allgenes"
      ]
    },
    {
      "page": "AlvMac_allGO",
      "title": "Example of custom gene ontology annotations.",
      "topics": [
        "AlvMac_allGO"
      ]
    },
    {
      "page": "AlvMac_GOgenes",
      "title": "Example of custom mapping between gene ontology identifiers and gene features.",
      "topics": [
        "AlvMac_GOgenes"
      ]
    },
    {
      "page": "AlvMac_results",
      "title": "Sample output from the 'GO_analyse()' function on an RNAseq experiment.",
      "topics": [
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      ]
    },
    {
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      "topics": [
        "AlvMac_results.pVal"
      ]
    },
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      "title": "Generates a hierarchical clustering of the samples",
      "topics": [
        "cluster_GO"
      ]
    },
    {
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      "title": "Plots the expression profile of a gene by levels of a factor",
      "topics": [
        "expression_plot"
      ]
    },
    {
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      "title": "Plots the expression profile of a gene by levels of a factor",
      "topics": [
        "expression_plot_symbol"
      ]
    },
    {
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      "title": "Plots the individual expression profile of a gene in samples series",
      "topics": [
        "expression_profiles"
      ]
    },
    {
      "page": "expression_profiles_symbol",
      "title": "Plots the individual expression profile of a gene in samples series",
      "topics": [
        "expression_profiles_symbol"
      ]
    },
    {
      "page": "GO_analyse",
      "title": "Identifies gene ontologies clustering samples according to predefined factor.",
      "topics": [
        "GO_analyse"
      ]
    },
    {
      "page": "heatmap_GO",
      "title": "Generates a heatmap and hierarchical clustering of the samples and the genes",
      "topics": [
        "heatmap_GO"
      ]
    },
    {
      "page": "hist_scores",
      "title": "Plots the distribution of scores following an GOexpress analysis.",
      "topics": [
        "hist_scores"
      ]
    },
    {
      "page": "list_genes",
      "title": "Returns the genes associated with a Gene Ontology",
      "topics": [
        "list_genes"
      ]
    },
    {
      "page": "microarray2dataset",
      "title": "Table mapping probeset identifier prefixes to datasets in the Ensembl BioMart.",
      "topics": [
        "microarray2dataset"
      ]
    },
    {
      "page": "plot_design",
      "title": "Plot Univariate Effects for genes associated with a Gene Ontology",
      "topics": [
        "plot_design"
      ]
    },
    {
      "page": "prefix2dataset",
      "title": "Table mapping Ensembl gene identifier prefixes to BioMart datasets.",
      "topics": [
        "prefix2dataset"
      ]
    },
    {
      "page": "pValue_GO",
      "title": "Compute p-values for ontologies by randomising gene labels.",
      "topics": [
        "pValue_GO"
      ]
    },
    {
      "page": "quantiles_scores",
      "title": "Returns the quantiles of scores following an GOexpress analysis.",
      "topics": [
        "quantiles_scores"
      ]
    },
    {
      "page": "rerank",
      "title": "Reorder the result variable by alternative metrics.",
      "topics": [
        "rerank"
      ]
    },
    {
      "page": "subEset",
      "title": "Subset an ExpressionSet to values of phenotypic data columns.",
      "topics": [
        "subEset"
      ]
    },
    {
      "page": "subset_scores",
      "title": "Returns a filtered list from GO_analyse results.",
      "topics": [
        "subset_scores"
      ]
    },
    {
      "page": "table_genes",
      "title": "Returns a table listing the genes associated with a given Gene Ontology",
      "topics": [
        "table_genes"
      ]
    }
  ],
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