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  "Package": "BPCells",
  "Title": "Single Cell Counts Matrices to PCA",
  "Version": "0.3.1",
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  "Description": "> Efficient operations for single cell ATAC-seq fragments\nand RNA counts matrices. Interoperable with standard file\nformats, and introduces efficient bit-packed formats that allow\nlarge storage savings and increased read speeds.",
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  "Config/pak/sysreqs": "libicu-dev libx11-dev",
  "Repository": "https://agshaas.r-universe.dev",
  "Date/Publication": "2026-10-26 06:24:38 UTC",
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  "Packaged": {
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  "Author": "Benjamin Parks [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0002-0261-7472>),\nImmanuel Abdi [aut],\nStanford University [cph, fnd],\nGenentech, Inc. [cph, fnd]",
  "Maintainer": "Benjamin Parks <bparks@alumni.stanford.edu>",
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  "_file": "BPCells_0.3.1.tar.gz",
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  "_created": "2026-10-26T06:52:29.000Z",
  "_published": "2026-10-26T07:44:56.189Z",
  "_upstream": "https://github.com/bnprks/BPCells",
  "_status": "success",
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    "canonical_gene_symbol",
    "cellNames",
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    "chrNames",
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    "cluster_graph_leiden",
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    "draw_trackplot_grid",
    "expm1_slow",
    "extend_ranges",
    "footprint",
    "fragments_identical",
    "gene_region",
    "gene_score_archr",
    "gene_score_tiles_archr",
    "gene_score_weights_archr",
    "get_demo_frags",
    "get_demo_mat",
    "get_trackplot_height",
    "import_matrix_market",
    "import_matrix_market_10x",
    "knn_annoy",
    "knn_hnsw",
    "knn_to_geodesic_graph",
    "knn_to_snn_graph",
    "log1p_slow",
    "marker_features",
    "match_gene_symbol",
    "matrix_stats",
    "matrix_type",
    "merge_cells",
    "merge_peaks_iterative",
    "min_by_col",
    "min_by_row",
    "min_scalar",
    "multiply_cols",
    "multiply_rows",
    "normalize_ranges",
    "nucleosome_counts",
    "open_fragments_10x",
    "open_fragments_dir",
    "open_fragments_hdf5",
    "open_matrix_10x_hdf5",
    "open_matrix_anndata_hdf5",
    "open_matrix_dir",
    "open_matrix_hdf5",
    "order_ranges",
    "peak_matrix",
    "plot_dot",
    "plot_embedding",
    "plot_fragment_length",
    "plot_read_count_knee",
    "plot_tf_footprint",
    "plot_tss_profile",
    "plot_tss_scatter",
    "prefix_cell_names",
    "pseudobulk_matrix",
    "qc_scATAC",
    "range_distance_to_nearest",
    "read_bed",
    "read_encode_blacklist",
    "read_gencode_genes",
    "read_gencode_transcripts",
    "read_gtf",
    "read_ucsc_chrom_sizes",
    "regress_out",
    "remove_demo_data",
    "rotate_x_labels",
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    "rowMaxs.IterableMatrix",
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    "sample_bernoulli",
    "sctransform_pearson",
    "select_cells",
    "select_chromosomes",
    "select_regions",
    "set_trackplot_height",
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    "shift_fragments",
    "storage_order",
    "subset_lengths",
    "svds",
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    "trackplot_bulk",
    "trackplot_combine",
    "trackplot_coverage",
    "trackplot_gene",
    "trackplot_genome_annotation",
    "trackplot_loop",
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    "transpose_storage_order",
    "write_fragments_10x",
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    "write_insertion_bed",
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      "title": "Gene Symbol Mapping data",
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      "class": [
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      "fields": [],
      "table": false,
      "tojson": true
    },
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      "object": "mouse_gene_mapping",
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      "fields": [],
      "table": false,
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      "topics": [
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        "add_rows",
        "multiply_cols",
        "multiply_rows"
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    },
    {
      "page": "all_matrix_inputs",
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      "topics": [
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        "all_matrix_inputs<-"
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    },
    {
      "page": "apply_by_row",
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      "topics": [
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        "apply_by_row"
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    },
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      "page": "binarize",
      "title": "Convert matrix elements to zeros and ones",
      "topics": [
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    },
    {
      "page": "call_peaks_macs",
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      "topics": [
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      ]
    },
    {
      "page": "call_peaks_tile",
      "title": "Call peaks from tiles",
      "topics": [
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    },
    {
      "page": "checksum",
      "title": "Calculate the MD5 checksum of an IterableMatrix",
      "topics": [
        "checksum"
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    },
    {
      "page": "cluster_cells_graph",
      "title": "Cluster cell embeddings using a KNN graph-based algorithm",
      "topics": [
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    {
      "page": "cluster_graph",
      "title": "Cluster an adjacency matrix",
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        "cluster_graph_seurat"
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    },
    {
      "page": "cluster_membership_matrix",
      "title": "Convert grouping vector to sparse matrix",
      "topics": [
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    {
      "page": "collect_features",
      "title": "Collect features for plotting",
      "topics": [
        "collect_features"
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    },
    {
      "page": "convert_matrix_type",
      "title": "Convert the type of a matrix",
      "topics": [
        "convert_matrix_type"
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    },
    {
      "page": "fragment_R_conversion",
      "title": "Convert between BPCells fragments and R objects.",
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    {
      "page": "palettes",
      "title": "Color palettes",
      "topics": [
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        "discrete_palette"
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    },
    {
      "page": "extend_ranges",
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      "topics": [
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    },
    {
      "page": "footprint",
      "title": "Get footprints around a set of genomic coordinates",
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    {
      "page": "fragments_identical",
      "title": "Check if two fragments objects are identical",
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    },
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      "page": "gene_region",
      "title": "Find gene region",
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    {
      "page": "gene_score_tiles_archr",
      "title": "Calculate gene-tile distances for ArchR gene activities",
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    },
    {
      "page": "gene_scores",
      "title": "Calculate GeneActivityScores",
      "topics": [
        "gene_score_archr",
        "gene_score_weights_archr"
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    },
    {
      "page": "genomic-ranges-like",
      "title": "Genomic range formats",
      "topics": [
        "genomic-ranges-like"
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    },
    {
      "page": "demo_data",
      "title": "Retrieve BPCells demo data",
      "topics": [
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        "get_demo_mat",
        "remove_demo_data"
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    },
    {
      "page": "gene_mapping",
      "title": "Gene Symbol Mapping data",
      "topics": [
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        "mouse_gene_mapping"
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    },
    {
      "page": "import_matrix_market",
      "title": "Import MatrixMarket files",
      "topics": [
        "import_matrix_market",
        "import_matrix_market_10x"
      ]
    },
    {
      "page": "IterableFragments-methods",
      "title": "IterableFragments methods",
      "topics": [
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        "cellNames<-",
        "chrNames",
        "chrNames<-",
        "IterableFragments-methods",
        "show,IterableFragments-method"
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    {
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        "*,IterableMatrix,numeric-method",
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        "-,IterableMatrix,numeric-method",
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      "page": "knn_graph",
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      "page": "marker_features",
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      "page": "gene_matching",
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      "page": "matrix_R_conversion",
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      "page": "matrix_stats",
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      "page": "merge_cells",
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        "min_scalar"
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      "page": "normalize_ranges",
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      "page": "nucleosome_counts",
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      "page": "open_fragments_10x",
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      "page": "open_matrix_10x_hdf5",
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      "page": "order_ranges",
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      "page": "peak_matrix",
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      "page": "plot_dot",
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    {
      "page": "plot_embedding",
      "title": "Plot UMAP or embeddings",
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    {
      "page": "plot_fragment_length",
      "title": "Fragment size distribution",
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    {
      "page": "plot_read_count_knee",
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      "topics": [
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      "page": "plot_tf_footprint",
      "title": "Plot TF footprint",
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      "page": "plot_tss_profile",
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    {
      "page": "plot_tss_scatter",
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    {
      "page": "prefix_cell_names",
      "title": "Add sample prefix to cell names",
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      "page": "pseudobulk_matrix",
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      "page": "qc_scATAC",
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      "page": "range_distance_to_nearest",
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      "page": "read_bed",
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      "page": "read_gtf",
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      "page": "read_ucsc_chrom_sizes",
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      "topics": [
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      "page": "regress_out",
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