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    "dr_plot_width",
    "filter_cells",
    "filter_data",
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    "get_color_scheme",
    "get_dr_point_size",
    "get_test_counts_matrix",
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    "initialize_seurat_object",
    "integrate_layers",
    "integrate_seurat_object",
    "load_sample_counts_matrix",
    "merge_metadata",
    "merge_seurat_objects",
    "normalize_counts",
    "normalize_data",
    "plot_cluster_markers_heatmap",
    "plot_cluster_markers_top",
    "plot_clusters",
    "plot_distribution",
    "plot_dr_feature",
    "plot_dr_group",
    "plot_dr_umap_clusters",
    "plot_metrics_correlations",
    "plot_metrics_distribution",
    "plot_var_genes_euler",
    "plot_var_genes_upset",
    "profile_object_size",
    "read_counts_file",
    "resolve_seurat_object",
    "run_dr",
    "run_pca",
    "run_tsne",
    "run_umap",
    "save_counts",
    "save_dr_plot",
    "save_metadata",
    "save_seurat_counts_matrix",
    "set_identity",
    "split_layers_by_batch",
    "transfer_labels",
    "variable_features_by_batch",
    "write_message"
  ],
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    {
      "page": "add_gene_class_percent",
      "title": "Add mitochondrial, ribosomal, and hemoglobin percentages to a Seurat object.",
      "topics": [
        "add_gene_class_percent"
      ]
    },
    {
      "page": "add_seurat_assay",
      "title": "Add assay to Seurat object.",
      "topics": [
        "add_seurat_assay"
      ]
    },
    {
      "page": "annotate_pan_human_azimuth",
      "title": "Annotate with Pan-human Azimuth",
      "topics": [
        "annotate_pan_human_azimuth"
      ]
    },
    {
      "page": "as_data_frame_seurat",
      "title": "Function to extract data from Seurat object.",
      "topics": [
        "as_data_frame_seurat"
      ]
    },
    {
      "page": "calculate_cluster_expression",
      "title": "Per-cluster average expression (non-log space) and summed raw counts.",
      "topics": [
        "calculate_cluster_expression"
      ]
    },
    {
      "page": "calculate_cluster_markers",
      "title": "Calculate cluster markers (versus all other clusters, or pairwise) and plot them.",
      "topics": [
        "calculate_cluster_markers"
      ]
    },
    {
      "page": "calculate_cluster_stats",
      "title": "Per-cluster cell counts and a joined metadata+embeddings table.",
      "topics": [
        "calculate_cluster_stats"
      ]
    },
    {
      "page": "calculate_clusters",
      "title": "Identify clusters of cells by graph-based clustering.",
      "topics": [
        "calculate_clusters",
        "calculate_clusters.Seurat"
      ]
    },
    {
      "page": "check_identity_column",
      "title": "Check identity of the Seurat object.",
      "topics": [
        "check_identity_column"
      ]
    },
    {
      "page": "cluster_seurat_object",
      "title": "Reduce dimensions, cluster, and plot the result.",
      "topics": [
        "cluster_seurat_object"
      ]
    },
    {
      "page": "create_color_vect",
      "title": "Function to create a color vector.",
      "topics": [
        "create_color_vect"
      ]
    },
    {
      "page": "create_seurat_object",
      "title": "Create a usable Seurat object from a sample.",
      "topics": [
        "create_seurat_object"
      ]
    },
    {
      "page": "differential_expression_per_cluster",
      "title": "Calculate differentially expressed genes within each subpopulation/cluster",
      "topics": [
        "differential_expression_per_cluster"
      ]
    },
    {
      "page": "dr_plot_width",
      "title": "Width for a reduction plot, widened so many legend labels stay legible.",
      "topics": [
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      ]
    },
    {
      "page": "filter_cells",
      "title": "Filter cells based on the number of genes, counts, and mitochondrial reads.",
      "topics": [
        "filter_cells"
      ]
    },
    {
      "page": "geneset_score",
      "title": "Get geneset scores.",
      "topics": [
        "geneset_score"
      ]
    },
    {
      "page": "get_color_scheme",
      "title": "Determine the color scheme.",
      "topics": [
        "get_color_scheme"
      ]
    },
    {
      "page": "get_dr_point_size",
      "title": "Determine the point size for reduced dimensions scatter plots (smaller for larger datasets).",
      "topics": [
        "get_dr_point_size"
      ]
    },
    {
      "page": "get_test_counts_matrix",
      "title": "Get an example counts matrix.",
      "topics": [
        "get_test_counts_matrix"
      ]
    },
    {
      "page": "import_mtx",
      "title": "Read in 10x Genomics Cell Ranger Matrix Market format data.",
      "topics": [
        "import_mtx"
      ]
    },
    {
      "page": "initialize_seurat_object",
      "title": "Create a new Seurat object from a matrix.",
      "topics": [
        "initialize_seurat_object"
      ]
    },
    {
      "page": "integrate_layers",
      "title": "Integrate the layers of a Seurat object.",
      "topics": [
        "integrate_layers"
      ]
    },
    {
      "page": "integrate_seurat_object",
      "title": "Integrate a merged Seurat object across batches.",
      "topics": [
        "integrate_seurat_object"
      ]
    },
    {
      "page": "merge_metadata",
      "title": "Function to merge two metadata tables together.",
      "topics": [
        "merge_metadata"
      ]
    },
    {
      "page": "merge_seurat_objects",
      "title": "Merge multiple Seurat objects into one.",
      "topics": [
        "merge_seurat_objects"
      ]
    },
    {
      "page": "normalize_counts",
      "title": "Normalize the counts, select variable features, and scale.",
      "topics": [
        "normalize_counts"
      ]
    },
    {
      "page": "plot_cluster_markers_heatmap",
      "title": "Heatmap of the top cluster markers, at several top-N cutoffs.",
      "topics": [
        "plot_cluster_markers_heatmap"
      ]
    },
    {
      "page": "plot_cluster_markers_top",
      "title": "Plot a gene list in multiple ways: UMAP, dot plot, violin, and per-cluster bar plot.",
      "topics": [
        "plot_cluster_markers_top"
      ]
    },
    {
      "page": "plot_clusters",
      "title": "Plot a cluster resolution on tSNE and UMAP.",
      "topics": [
        "plot_clusters"
      ]
    },
    {
      "page": "plot_distribution",
      "title": "Plot the distribution of specified features/variables.",
      "topics": [
        "plot_distribution"
      ]
    },
    {
      "page": "plot_dr_feature",
      "title": "Plot a single feature overlaid on a dimensionality reduction.",
      "topics": [
        "plot_dr_feature"
      ]
    },
    {
      "page": "plot_dr_group",
      "title": "Scatter plot of a reduction, colored by a grouping variable.",
      "topics": [
        "plot_dr_group"
      ]
    },
    {
      "page": "plot_dr_umap_clusters",
      "title": "Plot a UMAP colored by one or more cluster/grouping variables.",
      "topics": [
        "plot_dr_umap_clusters"
      ]
    },
    {
      "page": "plot_metrics_correlations",
      "title": "Scatter plots of the per-cell QC metrics against each other.",
      "topics": [
        "plot_metrics_correlations"
      ]
    },
    {
      "page": "plot_metrics_distribution",
      "title": "Violin plots of the per-cell QC metrics.",
      "topics": [
        "plot_metrics_distribution"
      ]
    },
    {
      "page": "plot_var_genes_euler",
      "title": "Euler diagram of the variable genes shared between batches.",
      "topics": [
        "plot_var_genes_euler"
      ]
    },
    {
      "page": "plot_var_genes_upset",
      "title": "UpSet plot of the variable genes shared between batches.",
      "topics": [
        "plot_var_genes_upset"
      ]
    },
    {
      "page": "profile_object_size",
      "title": "Report the size of an object's slots, largest first.",
      "topics": [
        "profile_object_size"
      ]
    },
    {
      "page": "read_counts_file",
      "title": "Read in Gene Expression and Antibody Capture data from a 10x Genomics Cell Ranger sparse matrix or from a text file.",
      "topics": [
        "read_counts_file"
      ]
    },
    {
      "page": "resolve_seurat_object",
      "title": "Resolve a Seurat object, given either the object itself or a path to one on disk.",
      "topics": [
        "resolve_seurat_object"
      ]
    },
    {
      "page": "run_dr",
      "title": "Run dimensionality reduction: pca, tsne, or umap",
      "topics": [
        "run_dr"
      ]
    },
    {
      "page": "run_pca",
      "title": "Run PCA",
      "topics": [
        "run_pca",
        "run_pca.default",
        "run_pca.Seurat"
      ]
    },
    {
      "page": "run_tsne",
      "title": "Run TSNE",
      "topics": [
        "run_tsne",
        "run_tsne.default",
        "run_tsne.Seurat"
      ]
    },
    {
      "page": "run_umap",
      "title": "Run UMAP",
      "topics": [
        "run_umap",
        "run_umap.default",
        "run_umap.Seurat"
      ]
    },
    {
      "page": "save_counts",
      "title": "Save the counts matrix as a single table.",
      "topics": [
        "save_counts"
      ]
    },
    {
      "page": "save_dr_plot",
      "title": "Save a reduction plot, widened to fit its own legend.",
      "topics": [
        "save_dr_plot"
      ]
    },
    {
      "page": "save_metadata",
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      "topics": [
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    },
    {
      "page": "set_identity",
      "title": "Set identity of the Seurat object.",
      "topics": [
        "set_identity"
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    },
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      "page": "split_layers_by_batch",
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      "page": "transfer_labels",
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    },
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      "page": "variable_features_by_batch",
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      "topics": [
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      ]
    },
    {
      "page": "write_message",
      "title": "Small function to write to message and to log file.",
      "topics": [
        "write_message"
      ]
    }
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