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  "Type": "Package",
  "Package": "cardelino",
  "Title": "Clone Identification from Single Cell Data",
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  "Authors@R": "c(person(given = \"Jeffrey\",\nfamily = \"Pullin\",\nrole = \"aut\",\nemail = \"jpullin@svi.edu.au\"),\nperson(given = \"Yuanhua\",\nfamily = \"Huang\",\nrole = \"aut\",\nemail = \"yuanhua@hku.hk\"),\nperson(given = \"Davis\",\nfamily = \"McCarthy\",\nrole = c(\"aut\", \"cre\"),\nemail = \"dmccarthy@svi.edu.au\"))",
  "Description": "Methods to infer clonal tree configuration for a\npopulation of cells using single-cell RNA-seq data (scRNA-seq),\nand possibly other data modalities. Methods are also provided\nto assign cells to inferred clones and explore differences in\ngene expression between clones. These methods can flexibly\nintegrate information from imperfect clonal trees inferred\nbased on bulk exome-seq data, and sparse variant alleles\nexpressed in scRNA-seq data. A flexible beta-binomial error\nmodel that accounts for stochastic dropout events as well as\nsystematic allelic imbalance is used.",
  "License": "GPL-3",
  "URL": "https://github.com/single-cell-genetics/cardelino",
  "BugReports": "https://github.com/single-cell-genetics/cardelino/issues",
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:59:16 UTC",
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  "Author": "Jeffrey Pullin [aut],\nYuanhua Huang [aut],\nDavis McCarthy [aut, cre]",
  "Maintainer": "Davis McCarthy <dmccarthy@svi.edu.au>",
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  "_created": "2026-10-10T13:40:45.000Z",
  "_published": "2026-10-10T13:51:29.350Z",
  "_buildurl": "https://github.com/r-universe/bioc/actions/runs/38056327311",
  "_status": "success",
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  "_commit": {
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    "committer": "A Wokaty <andres.wokaty@sph.cuny.edu>",
    "message": "bump x.y.z version to odd y following creation of RELEASE_3_23 branch\n",
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    "assign_scores",
    "binaryPRC",
    "binaryROC",
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    "clone_id_EM",
    "clone_id_Gibbs",
    "colMatch",
    "donor_read_simulator",
    "get_snp_matrices",
    "get_tree",
    "heat_matrix",
    "load_cellSNP_vcf",
    "load_GT_vcf",
    "mixBinom",
    "mtx_to_df",
    "multiPRC",
    "plot_config_diffs",
    "plot_tree",
    "predMixBinom",
    "prob_heatmap",
    "pub.theme",
    "read_vcf",
    "rowArgmax",
    "rowMax",
    "sample_seq_depth",
    "sample_tree_SNV",
    "sim_read_count",
    "vc_heatmap"
  ],
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      "name": "A_clone",
      "title": "A matrix of read numbers of alternative alleles for clone ID",
      "object": "example_donor",
      "file": "example_donor.RData",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [],
      "rows": 34,
      "table": true,
      "tojson": true
    },
    {
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      "title": "A matrix of read numbers of alternative alleles",
      "object": "example_donor",
      "file": "example_donor.RData",
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        "matrix",
        "array"
      ],
      "fields": [],
      "rows": 34,
      "table": true,
      "tojson": true
    },
    {
      "name": "Config_all",
      "title": "A list of tree configuration",
      "object": "config_all",
      "file": "config_all.RData",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "D_clone",
      "title": "A matrix of sequencing depths for clone ID",
      "object": "example_donor",
      "file": "example_donor.RData",
      "class": [
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        "array"
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      "fields": [],
      "rows": 34,
      "table": true,
      "tojson": true
    },
    {
      "name": "D_germline",
      "title": "A matrix of sequencing depths",
      "object": "example_donor",
      "file": "example_donor.RData",
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        "matrix",
        "array"
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      "fields": [],
      "rows": 34,
      "table": true,
      "tojson": true
    },
    {
      "name": "D_input",
      "title": "A matrix of sequencing depths",
      "object": "simulation_input",
      "file": "simulation_input.RData",
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        "array"
      ],
      "fields": [
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      "title": "A tree object",
      "object": "example_donor",
      "file": "example_donor.RData",
      "class": [
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      "fields": [],
      "table": false,
      "tojson": false
    },
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      "name": "tree_3clone",
      "title": "A tree object",
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      "file": "simulation_input.RData",
      "class": [
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      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "tree_4clone",
      "title": "A tree object",
      "object": "simulation_input",
      "file": "simulation_input.RData",
      "class": [
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      "fields": [],
      "table": false,
      "tojson": false
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    {
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      "title": "A tree object",
      "object": "simulation_input",
      "file": "simulation_input.RData",
      "class": [
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      "fields": [],
      "table": false,
      "tojson": false
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  "_help": [
    {
      "page": "A_clone",
      "title": "A matrix of read numbers of alternative alleles for clone ID",
      "topics": [
        "A_clone"
      ]
    },
    {
      "page": "A_germline",
      "title": "A matrix of read numbers of alternative alleles",
      "topics": [
        "A_germline"
      ]
    },
    {
      "page": "assign_cells_to_clones",
      "title": "Assign cells to clones from cardelino results",
      "topics": [
        "assign_cells_to_clones"
      ]
    },
    {
      "page": "assign_scores",
      "title": "Scoring the simulation in assignment of singlets and doublets",
      "topics": [
        "assign_scores"
      ]
    },
    {
      "page": "binaryPRC",
      "title": "Precision-recall curve for binary label prediction",
      "topics": [
        "binaryPRC"
      ]
    },
    {
      "page": "binaryROC",
      "title": "ROC curve for binary label prediction",
      "topics": [
        "binaryROC"
      ]
    },
    {
      "page": "clone_id",
      "title": "Infer clonal identity of single cells",
      "topics": [
        "Clone ID",
        "clone_id",
        "clone_id_EM",
        "clone_id_Gibbs"
      ]
    },
    {
      "page": "colMatch",
      "title": "Column match between two matrices by minimum mean absolute difference",
      "topics": [
        "colMatch"
      ]
    },
    {
      "page": "Config_all",
      "title": "A list of tree configuration",
      "topics": [
        "Config_all"
      ]
    },
    {
      "page": "D_clone",
      "title": "A matrix of sequencing depths for clone ID",
      "topics": [
        "D_clone"
      ]
    },
    {
      "page": "D_germline",
      "title": "A matrix of sequencing depths",
      "topics": [
        "D_germline"
      ]
    },
    {
      "page": "D_input",
      "title": "A matrix of sequencing depths",
      "topics": [
        "D_input"
      ]
    },
    {
      "page": "devianceIC",
      "title": "Deviance Information Criterion for cardelino model",
      "topics": [
        "devianceIC"
      ]
    },
    {
      "page": "donor_read_simulator",
      "title": "Reads simulator for donor identification",
      "topics": [
        "donor_read_simulator"
      ]
    },
    {
      "page": "get_logLik",
      "title": "Log likelihood of clone_id model It returns P(A, D | C, I, theta0, theta1)",
      "topics": [
        "get_logLik"
      ]
    },
    {
      "page": "get_snp_matrices",
      "title": "Get SNP data matrices from VCF object(s)",
      "topics": [
        "get_snp_matrices"
      ]
    },
    {
      "page": "get_tree",
      "title": "Get a clonal tree from a configuration matrix",
      "topics": [
        "get_tree"
      ]
    },
    {
      "page": "Geweke_Z",
      "title": "Geweke diagnostic for MCMC sampling.",
      "topics": [
        "Geweke_Z"
      ]
    },
    {
      "page": "heat_matrix",
      "title": "Plot heatmap from a matrix",
      "topics": [
        "heat_matrix"
      ]
    },
    {
      "page": "heatmap.theme",
      "title": "The theme of heatmaps for prob_heatmap and sites_heatmap",
      "topics": [
        "heatmap.theme"
      ]
    },
    {
      "page": "load_cellSNP_vcf",
      "title": "Load sparse matrices A and D from cellSNP VCF file with filtering SNPs",
      "topics": [
        "load_cellSNP_vcf"
      ]
    },
    {
      "page": "load_GT_vcf",
      "title": "Load genotype VCF into numeric values: 0, 1, or 2",
      "topics": [
        "load_GT_vcf"
      ]
    },
    {
      "page": "mixBinom",
      "title": "EM algorithm for estimating binomial mixture model",
      "topics": [
        "mixBinom"
      ]
    },
    {
      "page": "mtx_to_df",
      "title": "Convert a matrix to data frame",
      "topics": [
        "mtx_to_df"
      ]
    },
    {
      "page": "multiPRC",
      "title": "Precision-recall curve for multi-class prediction",
      "topics": [
        "multiPRC"
      ]
    },
    {
      "page": "plot_config_diffs",
      "title": "Define a publication-style plot theme",
      "topics": [
        "plot_config_diffs"
      ]
    },
    {
      "page": "plot_tree",
      "title": "Plot a phylogenetic tree",
      "topics": [
        "plot_tree"
      ]
    },
    {
      "page": "predMixBinom",
      "title": "Predicted probability from learned binomial mixture model",
      "topics": [
        "predMixBinom"
      ]
    },
    {
      "page": "prob_heatmap",
      "title": "Plot a heatmap for probability of clone assignment",
      "topics": [
        "prob_heatmap"
      ]
    },
    {
      "page": "pub.theme",
      "title": "Define a publication-style plot theme",
      "topics": [
        "pub.theme"
      ]
    },
    {
      "page": "read_vcf",
      "title": "Read a VCF file into R session",
      "topics": [
        "read_vcf"
      ]
    },
    {
      "page": "rowArgmax",
      "title": "Column index of the maximum value for each row in a matrix",
      "topics": [
        "rowArgmax"
      ]
    },
    {
      "page": "rowMax",
      "title": "Maximum value for each row in a matrix",
      "topics": [
        "rowMax"
      ]
    },
    {
      "page": "sample_seq_depth",
      "title": "Update matrix D with manually selected missing rate",
      "topics": [
        "sample_seq_depth"
      ]
    },
    {
      "page": "sample_tree_SNV",
      "title": "Down sample number of SNVs in the tree",
      "topics": [
        "sample_tree_SNV"
      ]
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