{
  "_id": "6a10aa7dacfb0bcc41cbf087",
  "Package": "CellMentor",
  "Type": "Package",
  "Title": "Supervised Non-negative Matrix Factorization for Dimensional\nReduction in Single-Cell Analysis",
  "Version": "1.1.2",
  "Authors@R": "person(\"Ekaterina\", \"Petrenko\", \nemail = \"petrenko.kate@icloud.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-3549-834X\"))",
  "Description": "Implements supervised cell type-aware non-negative matrix\nfactorization (NMF) for dimensional reduction in single-cell\nRNA sequencing analysis. The package provides methods for\nincorporating cell type information into the dimensionality\nreduction process, enabling improved visualization and\ndownstream analysis of single-cell data while preserving\nbiological structure. CellMentor employs a unique loss function\nthat simultaneously minimizes variation within known cell\npopulations while maximizing distinctions between different\ncell types, enabling effective transfer of learned patterns\nfrom labeled reference datasets to new unlabeled data.",
  "License": "Apache License (>= 2)",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.2",
  "VignetteBuilder": "knitr",
  "biocViews": "Software, SingleCell, Transcriptomics, DimensionReduction",
  "URL": "https://github.com/petrenkokate/CellMentor",
  "BugReports": "https://github.com/petrenkokate/CellMentor/issues",
  "Config/testthat/edition": "3",
  "Config/pak/sysreqs": "cmake libglpk-dev make libicu-dev libpng-dev\nlibuv1-dev libxml2-dev libssl-dev python3 zlib1g-dev",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-05-22 10:03:17 UTC",
  "RemoteUrl": "https://github.com/bioc/CellMentor",
  "RemoteRef": "HEAD",
  "RemoteSha": "52bfb5db78f2ce67c8e4f619ea1344b44a789d09",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-22 18:39:09 UTC",
    "User": "root"
  },
  "Author": "Ekaterina Petrenko [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-3549-834X>)",
  "Maintainer": "Ekaterina Petrenko <petrenko.kate@icloud.com>",
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  "_created": "2026-05-22T18:39:09.000Z",
  "_published": "2026-05-22T19:11:57.032Z",
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  "_commit": {
    "id": "52bfb5db78f2ce67c8e4f619ea1344b44a789d09",
    "author": "Petrenko Kate <petrenko.kate@icloud.com>",
    "committer": "Petrenko Kate <petrenko.kate@icloud.com>",
    "message": "bug fix: factor-coerce NMI inputs for aricode 1.1.0 in Bioc 3.24\n\ncalculate_performance() in R/helper_functions.R was passing\naricode::NMI() a character vector of cell-type labels and a numeric\nvector of cluster IDs. aricode 1.1.0 (currently shipping in\nBioconductor 3.24) tightened input handling and now routes mixed-type\narguments through sort_pairs(), which calls as.integer() on the\ncharacter argument — turning labels such as \"alpha\" into NA and\naborting with \"NA are not supported.\" Both grid-search\nconfigurations in the vignette therefore failed, cascading to\n\"All parameter configurations failed; cannot select best_params\"\non the Bioconductor build farm.\n\nCoerce both NMI inputs to factor so labels and clusters share a\nwell-defined integer encoding. This restores the vignette and\npreserves the score semantics (NMI is invariant to label coding).\n\nThis is the underlying cause that the previous fix (1.1.1) surfaced\nwith a clearer error message but did not address.\n\nVerified in bioconductor/bioconductor_docker:devel (R 4.6.0 /\nBioc 3.24):\n  R CMD build --keep-empty-dirs --no-resave-data --md5 CellMentor\n    → creating vignettes ... OK\n  R CMD check --no-manual CellMentor_1.1.2.tar.gz\n    → Status: OK\n",
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      "object": "ref_matrix_toy",
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  "_help": [
    {
      "page": "CellMentor",
      "title": "CellMentor: Cell-Type Aware Dimensionality Reduction for Single-Cell RNA-Seq",
      "topics": [
        "CellMentor-package",
        "CellMentor"
      ]
    },
    {
      "page": "cm_annotation",
      "title": "Access cell annotations from a CellMentor object",
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      ]
    },
    {
      "page": "cm_rank",
      "title": "Access the rank of a CellMentor object",
      "topics": [
        "cm_rank"
      ]
    },
    {
      "page": "CreateCSFNMFobject",
      "title": "Create CSFNMF Object for Cell Type Analysis",
      "topics": [
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      ]
    },
    {
      "page": "data_matrix",
      "title": "Access the query (data) matrix from a RefDataList object",
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      ]
    },
    {
      "page": "H",
      "title": "Access the H matrix",
      "topics": [
        "H"
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    },
    {
      "page": "hBaronDataset",
      "title": "Load Baron Human Pancreas Dataset",
      "topics": [
        "hBaronDataset"
      ]
    },
    {
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      "title": "Access the RefDataList from a CSFNMF object",
      "topics": [
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    {
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      "title": "Load Muraro Pancreas Dataset",
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      "title": "Tiny prebuilt CSFNMF object for accessors (optional)",
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      "title": "Project Data onto NMF Basis Matrix",
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      "engine": "knitr::rmarkdown",
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        "Comparison to Existing Methods",
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        "3. Run CellMentor with Hyperparameter Optimization",
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        "5. Integration with SingleCellExperiment",
        "Running CellMentor on Your Own Data",
        "Required Inputs",
        "Workflow",
        "Session Information",
        "References"
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