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  "Package": "clustifyr",
  "Title": "Classifier for Single-cell RNA-seq Using Cell Clusters",
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  "Description": "Package designed to aid in classifying cells from\nsingle-cell RNA sequencing data using external reference data\n(e.g., bulk RNA-seq, scRNA-seq, microarray, gene lists). A\nvariety of correlation based methods and gene list enrichment\nmethods are provided to assist cell type assignment.",
  "Authors@R": "c(person(given = \"Rui\",\nfamily = \"Fu\",\nrole = c(\"cre\", \"aut\"),\nemail = \"ray.sinensis@gmail.com\"),\nperson(given = \"Kent\",\nfamily = \"Riemondy\",\nrole =  \"aut\",\nemail = \"kent.riemondy@gmail.com\"),\nperson(given = \"Austin\",\nfamily = \"Gillen\",\nrole = \"ctb\",\nemail = \"austin.gillen@ucdenver.edu\"),\nperson(given = \"Chengzhe\",\nfamily = \"Tian\",\nrole = \"ctb\",\nemail = \"Chengzhe.Tian@colorado.edu\"),\nperson(given = \"Jay\",\nfamily = \"Hesselberth\",\nrole = \"ctb\",\nemail = \"jay.hesselberth@gmail.com\"),\nperson(given = \"Yue\",\nfamily = \"Hao\",\nrole = \"ctb\",\nemail = \"haoyuethink@gmail.com\"),\nperson(given = \"Michelle\",\nfamily = \"Daya\",\nrole = \"ctb\",\nemail = \"michelle.daya@ucdenver.edu\"),\nperson(given = \"Sidhant\",\nfamily = \"Puntambekar\",\nrole = \"ctb\",\nemail = \"sidhantnp@yahoo.com\"),\nperson(\"RNA Bioscience Initiative\", role = c(\"fnd\", \"cph\"),\ncomment = c(ROR = \"https://ror.org/03wmf1y16\"))\n)",
  "License": "MIT + file LICENSE",
  "biocViews": "SingleCell, Annotation, Sequencing, Microarray,\nGeneExpression",
  "BugReports": "https://github.com/rnabioco/clustifyr/issues",
  "URL": "https://github.com/rnabioco/clustifyr,\nhttps://rnabioco.github.io/clustifyr/",
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:51:50 UTC",
  "RemoteUrl": "https://github.com/bioc/clustifyr",
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  "Packaged": {
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  "Author": "Rui Fu [cre, aut],\nKent Riemondy [aut],\nAustin Gillen [ctb],\nChengzhe Tian [ctb],\nJay Hesselberth [ctb],\nYue Hao [ctb],\nMichelle Daya [ctb],\nSidhant Puntambekar [ctb],\nRNA Bioscience Initiative [fnd, cph] (ROR: <https://ror.org/03wmf1y16>)",
  "Maintainer": "Rui Fu <ray.sinensis@gmail.com>",
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    "assess_rank_bias",
    "average_clusters",
    "binarize_expr",
    "build_atlas",
    "calc_distance",
    "calculate_pathway_gsea",
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    "call_to_metadata",
    "check_raw_counts",
    "clustify",
    "clustify_lists",
    "clustify_nudge",
    "clustifyr_methods",
    "collapse_to_cluster",
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    "cor_to_call",
    "cor_to_call_rank",
    "cor_to_call_topn",
    "downsample_matrix",
    "feature_select_PCA",
    "file_marker_parse",
    "find_rank_bias",
    "gene_pct_markerm",
    "get_ucsc_reference",
    "get_vargenes",
    "gmt_to_list",
    "insert_meta_object",
    "make_comb_ref",
    "marker_select",
    "matrixize_markers",
    "object_data",
    "object_ref",
    "overcluster",
    "overcluster_test",
    "parse_loc_object",
    "plot_best_call",
    "plot_cor",
    "plot_cor_heatmap",
    "plot_dims",
    "plot_gene",
    "plot_pathway_gsea",
    "plot_rank_bias",
    "pos_neg_marker",
    "pos_neg_select",
    "query_rank_bias",
    "ref_feature_select",
    "ref_marker_select",
    "reverse_marker_matrix",
    "run_clustifyr_app",
    "run_gsea",
    "sce_pbmc",
    "seurat_meta",
    "seurat_ref",
    "so_pbmc",
    "write_meta"
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      "title": "reference marker matrix from seurat citeseq CBMC tutorial",
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      "class": [
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        "CD8 T",
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        "Naive CD4 T",
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        "CD34+",
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      "object": "cbmc_ref",
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      "fields": [
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        "pDCs"
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      "tojson": true
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      "object": "pbmc_matrix_small",
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      "object": "pbmc_meta",
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      "title": "Variable genes identified by Seurat from single-cell RNA-seq PBMCs.",
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      "class": [
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    {
      "page": "append_genes",
      "title": "Given a reference matrix and a list of genes, take the union of all genes in vector and genes in reference matrix and insert zero counts for all remaining genes.",
      "topics": [
        "append_genes"
      ]
    },
    {
      "page": "assess_rank_bias",
      "title": "Find rank bias",
      "topics": [
        "assess_rank_bias"
      ]
    },
    {
      "page": "assign_ident",
      "title": "manually change idents as needed",
      "topics": [
        "assign_ident"
      ]
    },
    {
      "page": "average_clusters",
      "title": "Average expression values per cluster",
      "topics": [
        "average_clusters"
      ]
    },
    {
      "page": "binarize_expr",
      "title": "Binarize scRNAseq data",
      "topics": [
        "binarize_expr"
      ]
    },
    {
      "page": "build_atlas",
      "title": "Function to combine records into single atlas",
      "topics": [
        "build_atlas"
      ]
    },
    {
      "page": "calc_distance",
      "title": "Distance calculations for spatial coord",
      "topics": [
        "calc_distance"
      ]
    },
    {
      "page": "calc_similarity",
      "title": "compute similarity",
      "topics": [
        "calc_similarity"
      ]
    },
    {
      "page": "calculate_pathway_gsea",
      "title": "Convert expression matrix to GSEA pathway scores (would take a similar place in workflow before average_clusters/binarize)",
      "topics": [
        "calculate_pathway_gsea"
      ]
    },
    {
      "page": "call_consensus",
      "title": "get concensus calls for a list of cor calls",
      "topics": [
        "call_consensus"
      ]
    },
    {
      "page": "call_to_metadata",
      "title": "Insert called ident results into metadata",
      "topics": [
        "call_to_metadata"
      ]
    },
    {
      "page": "cbmc_m",
      "title": "reference marker matrix from seurat citeseq CBMC tutorial",
      "concept": [
        "data"
      ],
      "topics": [
        "cbmc_m"
      ]
    },
    {
      "page": "cbmc_ref",
      "title": "reference matrix from seurat citeseq CBMC tutorial",
      "concept": [
        "data"
      ],
      "topics": [
        "cbmc_ref"
      ]
    },
    {
      "page": "check_raw_counts",
      "title": "Given a count matrix, determine if the matrix has been either log-normalized, normalized, or contains raw counts",
      "topics": [
        "check_raw_counts"
      ]
    },
    {
      "page": "clustify",
      "title": "Compare scRNA-seq data to reference data.",
      "topics": [
        "clustify",
        "clustify.default",
        "clustify.Seurat",
        "clustify.SingleCellExperiment"
      ]
    },
    {
      "page": "clustify_lists",
      "title": "Main function to compare scRNA-seq data to gene lists.",
      "topics": [
        "clustify_lists",
        "clustify_lists.default",
        "clustify_lists.Seurat",
        "clustify_lists.SingleCellExperiment"
      ]
    },
    {
      "page": "clustify_nudge",
      "title": "Combined function to compare scRNA-seq data to bulk RNA-seq data and marker list",
      "topics": [
        "clustify_nudge",
        "clustify_nudge.default",
        "clustify_nudge.Seurat"
      ]
    },
    {
      "page": "clustifyr_methods",
      "title": "Correlation functions available in clustifyr",
      "topics": [
        "clustifyr_methods"
      ]
    },
    {
      "page": "collapse_to_cluster",
      "title": "From per-cell calls, take highest freq call in each cluster",
      "topics": [
        "collapse_to_cluster"
      ]
    },
    {
      "page": "compare_lists",
      "title": "Calculate adjusted p-values for hypergeometric test of gene lists or jaccard index",
      "topics": [
        "compare_lists"
      ]
    },
    {
      "page": "cor_to_call",
      "title": "get best calls for each cluster",
      "topics": [
        "cor_to_call"
      ]
    },
    {
      "page": "cor_to_call_rank",
      "title": "get ranked calls for each cluster",
      "topics": [
        "cor_to_call_rank"
      ]
    },
    {
      "page": "cor_to_call_topn",
      "title": "get top calls for each cluster",
      "topics": [
        "cor_to_call_topn"
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    },
    {
      "page": "cosine",
      "title": "Cosine distance",
      "topics": [
        "cosine"
      ]
    },
    {
      "page": "downrefs",
      "title": "table of references stored in clustifyrdata",
      "concept": [
        "data"
      ],
      "topics": [
        "downrefs"
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    },
    {
      "page": "downsample_matrix",
      "title": "downsample matrix by cluster or completely random",
      "topics": [
        "downsample_matrix"
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    },
    {
      "page": "feature_select_PCA",
      "title": "Returns a list of variable genes based on PCA",
      "topics": [
        "feature_select_PCA"
      ]
    },
    {
      "page": "file_marker_parse",
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      "topics": [
        "file_marker_parse"
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    },
    {
      "page": "find_rank_bias",
      "title": "Find rank bias",
      "topics": [
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    {
      "page": "gene_pct",
      "title": "pct of cells in each cluster that express genelist",
      "topics": [
        "gene_pct"
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    },
    {
      "page": "gene_pct_markerm",
      "title": "pct of cells in every cluster that express a series of genelists",
      "topics": [
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    },
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      "page": "get_best_match_matrix",
      "title": "Function to make best call from correlation matrix",
      "topics": [
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    {
      "page": "get_best_str",
      "title": "Function to make call and attach score",
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    {
      "page": "get_common_elements",
      "title": "Find entries shared in all vectors",
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      "page": "get_similarity",
      "title": "Compute similarity of matrices",
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      "page": "get_ucsc_reference",
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      "page": "get_unique_column",
      "title": "Generate a unique column id for a dataframe",
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    {
      "page": "get_vargenes",
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      "page": "gmt_to_list",
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      "page": "insert_meta_object",
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    {
      "page": "kl_divergence",
      "title": "KL divergence",
      "topics": [
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    },
    {
      "page": "make_comb_ref",
      "title": "make combination ref matrix to assess intermixing",
      "topics": [
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    },
    {
      "page": "marker_select",
      "title": "decide for one gene whether it is a marker for a certain cell type",
      "topics": [
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    },
    {
      "page": "matrixize_markers",
      "title": "Convert candidate genes list into matrix",
      "topics": [
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      "title": "Vector of mouse genes for 10x cellranger pipeline",
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      "page": "not_pretty_palette",
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      "page": "object_data",
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        "object_data.SingleCellExperiment"
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      "page": "object_loc_lookup",
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      "page": "object_ref",
      "title": "Function to convert labelled object to avg expression matrix",
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        "object_ref.Seurat",
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      "page": "overcluster",
      "title": "Overcluster by kmeans per cluster",
      "topics": [
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    {
      "page": "overcluster_test",
      "title": "compare clustering parameters and classification outcomes",
      "topics": [
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    {
      "page": "parse_loc_object",
      "title": "more flexible parsing of single cell objects",
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      "title": "Marker genes identified by Seurat from single-cell RNA-seq PBMCs.",
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    {
      "page": "percent_clusters",
      "title": "Percentage detected per cluster",
      "topics": [
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    {
      "page": "permute_similarity",
      "title": "Compute a p-value for similarity using permutation",
      "topics": [
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    {
      "page": "plot_best_call",
      "title": "Plot best calls for each cluster on a tSNE or umap",
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      "page": "plot_rank_bias",
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