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  "Title": "Analysis of single-cell epigenomics datasets with a Shiny App",
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  "Date/Publication": "2026-04-28 12:53:54 UTC",
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    {
      "page": "annotation_from_merged_peaks",
      "title": "Find nearest peaks of each gene and return refined annotation",
      "topics": [
        "annotation_from_merged_peaks"
      ]
    },
    {
      "page": "annotToCol2",
      "title": "annotToCol2",
      "topics": [
        "annotToCol2"
      ]
    },
    {
      "page": "anocol_binary",
      "title": "Helper binary column for anocol function",
      "topics": [
        "anocol_binary"
      ]
    },
    {
      "page": "anocol_categorical",
      "title": "Helper binary column for anocol function",
      "topics": [
        "anocol_categorical"
      ]
    },
    {
      "page": "bams_to_matrix_indexes",
      "title": "Count bam files on interval to create count indexes",
      "topics": [
        "bams_to_matrix_indexes"
      ]
    },
    {
      "page": "beds_to_matrix_indexes",
      "title": "Count bed files on interval to create count indexes",
      "topics": [
        "beds_to_matrix_indexes"
      ]
    },
    {
      "page": "calculate_CNA",
      "title": "Estimate copy number alterations in cytobands",
      "topics": [
        "calculate_CNA"
      ]
    },
    {
      "page": "calculate_cyto_mat",
      "title": "Calculate Fraction of reads in each cytobands",
      "topics": [
        "calculate_cyto_mat"
      ]
    },
    {
      "page": "calculate_gain_or_loss",
      "title": "Estimate the copy gains/loss of tumor vs normal based on log2-ratio of fraction of reads",
      "topics": [
        "calculate_gain_or_loss"
      ]
    },
    {
      "page": "calculate_logRatio_CNA",
      "title": "Calculate the log2-ratio of tumor vs normal fraction of reads in cytobands",
      "topics": [
        "calculate_logRatio_CNA"
      ]
    },
    {
      "page": "call_macs2_merge_peaks",
      "title": "Calling MACS2 peak caller and merging resulting peaks",
      "topics": [
        "call_macs2_merge_peaks"
      ]
    },
    {
      "page": "ce11.chromosomes",
      "title": "Data.frame of chromosome length - ce11",
      "topics": [
        "ce11.chromosomes"
      ]
    },
    {
      "page": "ce11.GeneTSS",
      "title": "Data.frame of gene TSS - ce11",
      "topics": [
        "ce11.GeneTSS"
      ]
    },
    {
      "page": "changeRange",
      "title": "changeRange",
      "topics": [
        "changeRange"
      ]
    },
    {
      "page": "CheA3_TF_nTargets",
      "title": "A data.frame with the number of targets of each TF in ChEA3",
      "topics": [
        "CheA3_TF_nTargets"
      ]
    },
    {
      "page": "check_correct_datamatrix",
      "title": "Check if matrix rownames are well formated and correct if needed",
      "topics": [
        "check_correct_datamatrix"
      ]
    },
    {
      "page": "choose_cluster_scExp",
      "title": "Choose a number of clusters",
      "topics": [
        "choose_cluster_scExp"
      ]
    },
    {
      "page": "choose_perplexity",
      "title": "Choose perplexity depending on number of cells for Tsne",
      "topics": [
        "choose_perplexity"
      ]
    },
    {
      "page": "col2hex",
      "title": "Col2Hex",
      "topics": [
        "col2hex"
      ]
    },
    {
      "page": "colors_scExp",
      "title": "Adding colors to cells & features",
      "topics": [
        "colors_scExp"
      ]
    },
    {
      "page": "combine_datamatrix",
      "title": "Combine two matrices and emit warning if no regions are in common",
      "topics": [
        "combine_datamatrix"
      ]
    },
    {
      "page": "combine_enrichmentTests",
      "title": "Run enrichment tests and combine into list",
      "topics": [
        "combine_enrichmentTests"
      ]
    },
    {
      "page": "comparable_variables",
      "title": "Find comparable variable scExp",
      "topics": [
        "comparable_variables"
      ]
    },
    {
      "page": "CompareedgeRGLM",
      "title": "Creates a summary table with the number of genes under- or overexpressed in each group and outputs several graphical representations",
      "topics": [
        "CompareedgeRGLM"
      ]
    },
    {
      "page": "CompareWilcox",
      "title": "CompareWilcox",
      "topics": [
        "CompareWilcox"
      ]
    },
    {
      "page": "concatenate_scBed_into_clusters",
      "title": "Concatenate single-cell BED into clusters",
      "topics": [
        "concatenate_scBed_into_clusters"
      ]
    },
    {
      "page": "consensus_clustering_scExp",
      "title": "Wrapper to apply ConsensusClusterPlus to scExp object",
      "topics": [
        "consensus_clustering_scExp"
      ]
    },
    {
      "page": "correlation_and_hierarchical_clust_scExp",
      "title": "Correlation and hierarchical clustering",
      "topics": [
        "correlation_and_hierarchical_clust_scExp"
      ]
    },
    {
      "page": "count_coverage",
      "title": "Create a smoothed and normalized coverage track from a BAM file and given a bin GenomicRanges object (same as deepTools bamCoverage)",
      "topics": [
        "count_coverage"
      ]
    },
    {
      "page": "create_project_folder",
      "title": "Create ChromSCape project folder",
      "topics": [
        "create_project_folder"
      ]
    },
    {
      "page": "create_sample_name_mat",
      "title": "Create a sample name matrix",
      "topics": [
        "create_sample_name_mat"
      ]
    },
    {
      "page": "create_scDataset_raw",
      "title": "Create a simulated single cell datamatrix & cell annotation",
      "topics": [
        "create_scDataset_raw"
      ]
    },
    {
      "page": "create_scExp",
      "title": "Wrapper to create the single cell experiment from count matrix and feature dataframe",
      "topics": [
        "create_scExp"
      ]
    },
    {
      "page": "DA_custom",
      "title": "Differential Analysis Custom in 'One vs One' mode",
      "topics": [
        "DA_custom"
      ]
    },
    {
      "page": "DA_one_vs_rest",
      "title": "Differential Analysis in 'One vs Rest' mode",
      "topics": [
        "DA_one_vs_rest"
      ]
    },
    {
      "page": "DA_pairwise",
      "title": "Run differential analysis in Pairwise mode",
      "topics": [
        "DA_pairwise"
      ]
    },
    {
      "page": "define_feature",
      "title": "Define the features on which reads will be counted",
      "topics": [
        "define_feature"
      ]
    },
    {
      "page": "detect_samples",
      "title": "Heuristic discovery of samples based on cell labels",
      "topics": [
        "detect_samples"
      ]
    },
    {
      "page": "differential_activation",
      "title": "Find Differentialy Activated Features (One vs All)",
      "topics": [
        "differential_activation"
      ]
    },
    {
      "page": "differential_analysis_scExp",
      "title": "Runs differential analysis between cell clusters",
      "topics": [
        "differential_analysis_scExp"
      ]
    },
    {
      "page": "distPearson",
      "title": "distPearson",
      "topics": [
        "distPearson"
      ]
    },
    {
      "page": "enrich_TF_ChEA3_genes",
      "title": "Find the TF that are enriched in the differential genes using ChEA3 API",
      "topics": [
        "enrich_TF_ChEA3_genes"
      ]
    },
    {
      "page": "enrich_TF_ChEA3_scExp",
      "title": "Find the TF that are enriched in the differential genes using ChEA3 database",
      "topics": [
        "enrich_TF_ChEA3_scExp"
      ]
    },
    {
      "page": "enrichmentTest",
      "title": "enrichmentTest",
      "topics": [
        "enrichmentTest"
      ]
    },
    {
      "page": "exclude_features_scExp",
      "title": "Remove specific features (CNA, repeats)",
      "topics": [
        "exclude_features_scExp"
      ]
    },
    {
      "page": "feature_annotation_scExp",
      "title": "Add gene annotations to features",
      "topics": [
        "feature_annotation_scExp"
      ]
    },
    {
      "page": "filter_correlated_cell_scExp",
      "title": "Filter lowly correlated cells",
      "topics": [
        "filter_correlated_cell_scExp"
      ]
    },
    {
      "page": "filter_genes_with_refined_peak_annotation",
      "title": "Filter genes based on peak calling refined annotation",
      "topics": [
        "filter_genes_with_refined_peak_annotation"
      ]
    },
    {
      "page": "filter_scExp",
      "title": "Filter cells and features",
      "topics": [
        "filter_scExp"
      ]
    },
    {
      "page": "find_clusters_louvain_scExp",
      "title": "Build SNN graph and find cluster using Louvain Algorithm",
      "topics": [
        "find_clusters_louvain_scExp"
      ]
    },
    {
      "page": "find_top_features",
      "title": "Find most covered features",
      "topics": [
        "find_top_features"
      ]
    },
    {
      "page": "gene_set_enrichment_analysis_scExp",
      "title": "Runs Gene Set Enrichment Analysis on genes associated with differential features",
      "topics": [
        "gene_set_enrichment_analysis_scExp"
      ]
    },
    {
      "page": "generate_analysis",
      "title": "Generate a complete ChromSCape analysis",
      "topics": [
        "generate_analysis"
      ]
    },
    {
      "page": "generate_count_matrix",
      "title": "Generate count matrix",
      "topics": [
        "generate_count_matrix"
      ]
    },
    {
      "page": "generate_coverage_tracks",
      "title": "Generate cell cluster pseudo-bulk coverage tracks",
      "topics": [
        "generate_coverage_tracks"
      ]
    },
    {
      "page": "generate_feature_names",
      "title": "Generate feature names",
      "topics": [
        "generate_feature_names"
      ]
    },
    {
      "page": "generate_report",
      "title": "From a ChromSCape analysis directory, generate an HTML report.",
      "topics": [
        "generate_report"
      ]
    },
    {
      "page": "get_color_dataframe_from_input",
      "title": "Get color dataframe from shiny::colorInput",
      "topics": [
        "get_color_dataframe_from_input"
      ]
    },
    {
      "page": "get_cyto_features",
      "title": "Map features onto cytobands",
      "topics": [
        "get_cyto_features"
      ]
    },
    {
      "page": "get_genomic_coordinates",
      "title": "Get SingleCellExperiment's genomic coordinates",
      "topics": [
        "get_genomic_coordinates"
      ]
    },
    {
      "page": "get_most_variable_cyto",
      "title": "Retrieve the cytobands with the most variable fraction of reads",
      "topics": [
        "get_most_variable_cyto"
      ]
    },
    {
      "page": "get_pathway_mat_scExp",
      "title": "Get pathway matrix",
      "topics": [
        "get_pathway_mat_scExp"
      ]
    },
    {
      "page": "getExperimentNames",
      "title": "Get experiment names from a SingleCellExperiment",
      "topics": [
        "getExperimentNames"
      ]
    },
    {
      "page": "getMainExperiment",
      "title": "Get Main experiment of a SingleCellExperiment",
      "topics": [
        "getMainExperiment"
      ]
    },
    {
      "page": "gg_fill_hue",
      "title": "gg_fill_hue",
      "topics": [
        "gg_fill_hue"
      ]
    },
    {
      "page": "groupMat",
      "title": "groupMat",
      "topics": [
        "groupMat"
      ]
    },
    {
      "page": "H1proportion",
      "title": "H1proportion",
      "topics": [
        "H1proportion"
      ]
    },
    {
      "page": "has_genomic_coordinates",
      "title": "Does SingleCellExperiment has genomic coordinates in features ?",
      "topics": [
        "has_genomic_coordinates"
      ]
    },
    {
      "page": "hclustAnnotHeatmapPlot",
      "title": "hclustAnnotHeatmapPlot",
      "topics": [
        "hclustAnnotHeatmapPlot"
      ]
    },
    {
      "page": "hg38.chromosomes",
      "title": "Data.frame of chromosome length - hg38",
      "topics": [
        "hg38.chromosomes"
      ]
    },
    {
      "page": "hg38.cytoBand",
      "title": "Data.frame of cytoBandlocation - hg38",
      "topics": [
        "hg38.cytoBand"
      ]
    },
    {
      "page": "hg38.GeneTSS",
      "title": "Data.frame of gene TSS - hg38",
      "topics": [
        "hg38.GeneTSS"
      ]
    },
    {
      "page": "imageCol",
      "title": "imageCol",
      "topics": [
        "imageCol"
      ]
    },
    {
      "page": "import_count_input_files",
      "title": "Import and count input files depending on their format",
      "topics": [
        "import_count_input_files"
      ]
    },
    {
      "page": "import_scExp",
      "title": "Read single-cell matrix(ces) into scExp",
      "topics": [
        "import_scExp"
      ]
    },
    {
      "page": "index_peaks_barcodes_to_matrix_indexes",
      "title": "Read index-peaks-barcodes trio files on interval to create count indexes",
      "topics": [
        "index_peaks_barcodes_to_matrix_indexes"
      ]
    },
    {
      "page": "inter_correlation_scExp",
      "title": "Calculate inter correlation between cluster or samples",
      "topics": [
        "inter_correlation_scExp"
      ]
    },
    {
      "page": "intra_correlation_scExp",
      "title": "Calculate intra correlation between cluster or samples",
      "topics": [
        "intra_correlation_scExp"
      ]
    },
    {
      "page": "launchApp",
      "title": "Launch ChromSCape",
      "topics": [
        "launchApp"
      ]
    },
    {
      "page": "load_MSIGdb",
      "title": "Load and format MSIGdb pathways using msigdbr package",
      "topics": [
        "load_MSIGdb"
      ]
    },
    {
      "page": "merge_MACS2_peaks",
      "title": "Merge peak files from MACS2 peak caller",
      "topics": [
        "merge_MACS2_peaks"
      ]
    },
    {
      "page": "mm10.chromosomes",
      "title": "Data.frame of chromosome length - mm10",
      "topics": [
        "mm10.chromosomes"
      ]
    },
    {
      "page": "mm10.cytoBand",
      "title": "Data.frame of cytoBandlocation - mm10",
      "topics": [
        "mm10.cytoBand"
      ]
    },
    {
      "page": "mm10.GeneTSS",
      "title": "Data.frame of gene TSS - mm10",
      "topics": [
        "mm10.GeneTSS"
      ]
    },
    {
      "page": "normalize_scExp",
      "title": "Normalize counts",
      "topics": [
        "normalize_scExp"
      ]
    },
    {
      "page": "num_cell_after_cor_filt_scExp",
      "title": "Number of cells before & after correlation filtering",
      "topics": [
        "num_cell_after_cor_filt_scExp"
      ]
    },
    {
      "page": "num_cell_after_QC_filt_scExp",
      "title": "Table of cells before / after QC",
      "topics": [
        "num_cell_after_QC_filt_scExp"
      ]
    },
    {
      "page": "num_cell_before_cor_filt_scExp",
      "title": "Table of number of cells before correlation filtering",
      "topics": [
        "num_cell_before_cor_filt_scExp"
      ]
    },
    {
      "page": "num_cell_in_cluster_scExp",
      "title": "Number of cells in each cluster",
      "topics": [
        "num_cell_in_cluster_scExp"
      ]
    },
    {
      "page": "num_cell_scExp",
      "title": "Table of cells",
      "topics": [
        "num_cell_scExp"
      ]
    },
    {
      "page": "pca_irlba_for_sparseMatrix",
      "title": "Run sparse PCA using irlba SVD",
      "topics": [
        "pca_irlba_for_sparseMatrix"
      ]
    },
    {
      "page": "plot_cluster_consensus_scExp",
      "title": "Plot cluster consensus",
      "topics": [
        "plot_cluster_consensus_scExp"
      ]
    },
    {
      "page": "plot_correlation_PCA_scExp",
      "title": "Plotting correlation of PCs with a variable of interest",
      "topics": [
        "plot_correlation_PCA_scExp"
      ]
    },
    {
      "page": "plot_coverage_BigWig",
      "title": "Coverage plot",
      "topics": [
        "plot_coverage_BigWig"
      ]
    },
    {
      "page": "plot_differential_summary_scExp",
      "title": "Differential summary barplot",
      "topics": [
        "plot_differential_summary_scExp"
      ]
    },
    {
      "page": "plot_differential_volcano_scExp",
      "title": "Volcano plot of differential features",
      "topics": [
        "plot_differential_volcano_scExp"
      ]
    },
    {
      "page": "plot_distribution_scExp",
      "title": "Plotting distribution of signal",
      "topics": [
        "plot_distribution_scExp"
      ]
    },
    {
      "page": "plot_gain_or_loss_barplots",
      "title": "Plot Gain or Loss of cytobands of the most variables cytobands",
      "topics": [
        "plot_gain_or_loss_barplots"
      ]
    },
    {
      "page": "plot_heatmap_scExp",
      "title": "Plot cell correlation heatmap with annotations",
      "topics": [
        "plot_heatmap_scExp"
      ]
    },
    {
      "page": "plot_inter_correlation_scExp",
      "title": "Violin plot of inter-correlation distribution between one or multiple groups and one reference group",
      "topics": [
        "plot_inter_correlation_scExp"
      ]
    },
    {
      "page": "plot_intra_correlation_scExp",
      "title": "Violin plot of intra-correlation distribution",
      "topics": [
        "plot_intra_correlation_scExp"
      ]
    },
    {
      "page": "plot_most_contributing_features",
      "title": "Plot Top/Bottom most contributing features to PCA",
      "topics": [
        "plot_most_contributing_features"
      ]
    },
    {
      "page": "plot_percent_active_feature_scExp",
      "title": "Barplot of the % of active cells for a given features",
      "topics": [
        "plot_percent_active_feature_scExp"
      ]
    },
    {
      "page": "plot_pie_most_contributing_chr",
      "title": "Pie chart of top contribution of chromosomes in the 100 most contributing features to PCA #'",
      "topics": [
        "plot_pie_most_contributing_chr"
      ]
    },
    {
      "page": "plot_reduced_dim_scExp",
      "title": "Plot reduced dimensions (PCA, TSNE, UMAP)",
      "topics": [
        "plot_reduced_dim_scExp"
      ]
    },
    {
      "page": "plot_reduced_dim_scExp_CNA",
      "title": "Plot UMAP colored by Gain or Loss of cytobands",
      "topics": [
        "plot_reduced_dim_scExp_CNA"
      ]
    },
    {
      "page": "plot_top_TF_scExp",
      "title": "Barplot of top TFs from ChEA3 TF enrichment analysis",
      "topics": [
        "plot_top_TF_scExp"
      ]
    },
    {
      "page": "plot_violin_feature_scExp",
      "title": "Violin plot of features",
      "topics": [
        "plot_violin_feature_scExp"
      ]
    },
    {
      "page": "preprocess_CPM",
      "title": "Preprocess scExp - Counts Per Million (CPM)",
      "topics": [
        "preprocess_CPM"
      ]
    },
    {
      "page": "preprocess_feature_size_only",
      "title": "Preprocess scExp - size only",
      "topics": [
        "preprocess_feature_size_only"
      ]
    },
    {
      "page": "preprocess_RPKM",
      "title": "Preprocess scExp - Read per Kilobase Per Million (RPKM)",
      "topics": [
        "preprocess_RPKM"
      ]
    },
    {
      "page": "preprocess_TFIDF",
      "title": "Preprocess scExp - TF-IDF",
      "topics": [
        "preprocess_TFIDF"
      ]
    },
    {
      "page": "preprocess_TPM",
      "title": "Preprocess scExp - Transcripts per Million (TPM)",
      "topics": [
        "preprocess_TPM"
      ]
    },
    {
      "page": "preprocessing_filtering_and_reduction",
      "title": "Preprocess and filter matrix annotation data project folder to SCE",
      "topics": [
        "preprocessing_filtering_and_reduction"
      ]
    },
    {
      "page": "raw_counts_to_sparse_matrix",
      "title": "Create a sparse count matrix from various format of input data.",
      "topics": [
        "raw_counts_to_sparse_matrix"
      ]
    },
    {
      "page": "rawfile_ToBigWig",
      "title": "rawfile_ToBigWig : reads in BAM file and write out BigWig coverage file, normalized and smoothed",
      "topics": [
        "rawfile_ToBigWig"
      ]
    },
    {
      "page": "read_count_mat_with_separated_chr_start_end",
      "title": "Read a count matrix with three first columns (chr,start,end)",
      "topics": [
        "read_count_mat_with_separated_chr_start_end"
      ]
    },
    {
      "page": "read_sparse_matrix",
      "title": "Read in one or multiple sparse matrices (10X format)",
      "topics": [
        "read_sparse_matrix"
      ]
    },
    {
      "page": "rebin_helper",
      "title": "Rebin Helper for rebin_matrix function",
      "topics": [
        "rebin_helper"
      ]
    },
    {
      "page": "rebin_matrix",
      "title": "Transforms a bins x cells count matrix into a larger bins x cells count matrix.",
      "topics": [
        "rebin_matrix"
      ]
    },
    {
      "page": "reduce_dim_batch_correction",
      "title": "Reduce dimension with batch corrections",
      "topics": [
        "reduce_dim_batch_correction"
      ]
    },
    {
      "page": "reduce_dims_scExp",
      "title": "Reduce dimensions (PCA, TSNE, UMAP)",
      "topics": [
        "reduce_dims_scExp"
      ]
    },
    {
      "page": "remove_chr_M_fun",
      "title": "Remove chromosome M from scExprownames",
      "topics": [
        "remove_chr_M_fun"
      ]
    },
    {
      "page": "remove_non_canonical_fun",
      "title": "Remove non canonical chromosomes from scExp",
      "topics": [
        "remove_non_canonical_fun"
      ]
    },
    {
      "page": "results_enrichmentTest",
      "title": "Resutls of hypergeometric gene set enrichment test",
      "topics": [
        "results_enrichmentTest"
      ]
    },
    {
      "page": "retrieve_top_bot_features_pca",
      "title": "Retrieve Top and Bot most contributing features of PCA",
      "topics": [
        "retrieve_top_bot_features_pca"
      ]
    },
    {
      "page": "run_pairwise_tests",
      "title": "Run pairwise tests",
      "topics": [
        "run_pairwise_tests"
      ]
    },
    {
      "page": "run_tsne_scExp",
      "title": "Run tsne on single cell experiment",
      "topics": [
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