CompareWilcox           CompareWilcox
CompareedgeRGLM         Creates a summary table with the number of
                        genes under- or overexpressed in each group and
                        outputs several graphical representations
DA_custom               Differential Analysis in 'One vs Rest' mode
DA_one_vs_rest_fun      Differential Analysis in 'One vs Rest' mode
DA_pairwise             Run differential analysis in Pairwise mode
H1proportion            H1proportion
annotToCol2             annotToCol2
annotation_from_merged_peaks
                        Find nearest peaks of each gene and return
                        refined annotation
anocol_binary           Helper binary column for anocol function
anocol_categorical      Helper binary column for anocol function
bams_to_matrix_indexes
                        Count bam files on interval to create count
                        indexes
beds_to_matrix_indexes
                        Count bed files on interval to create count
                        indexes
calculate_CNA           Estimate copy number alterations in cytobands
calculate_cyto_mat      Calculate Fraction of reads in each cytobands
calculate_gain_or_loss
                        Estimate the copy gains/loss of tumor vs normal
                        based on log2-ratio of fraction of reads
calculate_logRatio_CNA
                        Calculate the log2-ratio of tumor vs normal
                        fraction of reads in cytobands
call_macs2_merge_peaks
                        Calling MACS2 peak caller and merging resulting
                        peaks
changeRange             changeRange
check_correct_datamatrix
                        Check if matrix rownames are well formated and
                        correct if needed
choose_cluster_scExp    Choose a number of clusters
choose_perplexity       Choose perplexity depending on number of cells
                        for Tsne
col2hex                 Col2Hex
colors_scExp            Adding colors to cells & features
combine_datamatrix      Combine two matrices and emit warning if no
                        regions are in common
combine_enrichmentTests
                        Run enrichment tests and combine into list
concatenate_scBed_into_clusters
                        Concatenate single-cell BED into clusters
consensus_clustering_scExp
                        Wrapper to apply ConsensusClusterPlus to scExp
                        object
correlation_and_hierarchical_clust_scExp
                        Correlation and hierarchical clustering
count_coverage          Create a smoothed and normalized coverage track
                        from a BAM file and given a bin GenomicRanges
                        object (same as deepTools bamCoverage)
create_project_folder   Create ChromSCape project folder
create_sample_name_mat
                        Create a sample name matrix
create_scDataset_raw    Create a simulated single cell datamatrix &
                        cell annotation
create_scExp            Wrapper to create the single cell experiment
                        from count matrix and feature dataframe
define_feature          Define the features on which reads will be
                        counted
detect_samples          Heuristic discovery of samples based on cell
                        labels
differential_analysis_scExp
                        Runs differential analysis between cell
                        clusters
distPearson             distPearson
enrichmentTest          enrichmentTest
exclude_features_scExp
                        Remove specific features (CNA, repeats)
feature_annotation_scExp
                        Add gene annotations to features
filter_correlated_cell_scExp
                        Filter lowly correlated cells
filter_genes_with_refined_peak_annotation
                        Filter genes based on peak calling refined
                        annotation
filter_scExp            Filter cells and features
find_top_features       Find most covered features
gene_set_enrichment_analysis_scExp
                        Runs Gene Set Enrichment Analysis on genes
                        associated with differential features
generate_analysis       Generate a complete ChromSCape analysis
generate_count_matrix   Generate count matrix
generate_coverage_tracks
                        Generate cell cluster pseudo-bulk coverage
                        tracks
generate_feature_names
                        Generate feature names
getExperimentNames      Get experiment names from a
                        SingleCellExperiment
getMainExperiment       Get Main experiment of a SingleCellExperiment
get_color_dataframe_from_input
                        Get color dataframe from shiny::colorInput
get_cyto_features       Map features onto cytobands
get_genomic_coordinates
                        Get SingleCellExperiment's genomic coordinates
get_most_variable_cyto
                        Retrieve the cytobands with the most variable
                        fraction of reads
gg_fill_hue             gg_fill_hue
groupMat                groupMat
has_genomic_coordinates
                        Does SingleCellExperiment has genomic
                        coordinates in features ?
hclustAnnotHeatmapPlot
                        hclustAnnotHeatmapPlot
hg38.GeneTSS            Data.frame of gene TSS - hg38
hg38.chromosomes        Data.frame of chromosome length - hg38
hg38.cytoBand           Data.frame of cytoBandlocation - hg38
imageCol                imageCol
import_count_input_files
                        Import and count input files depending on their
                        format
import_scExp            Read single-cell matrix(ces) into scExp
index_peaks_barcodes_to_matrix_indexes
                        Read index-peaks-barcodes trio files on
                        interval to create count indexes
inter_correlation_scExp
                        Calculate inter correlation between cluster or
                        samples
intra_correlation_scExp
                        Calculate intra correlation between cluster or
                        samples
launchApp               Launch ChromSCape
load_MSIGdb             Load and format MSIGdb pathways using msigdbr
                        package
merge_MACS2_peaks       Merge peak files from MACS2 peak caller
mm10.GeneTSS            Data.frame of gene TSS - mm10
mm10.chromosomes        Data.frame of chromosome length - mm10
mm10.cytoBand           Data.frame of cytoBandlocation - mm10
normalize_scExp         Normalize counts
num_cell_after_QC_filt_scExp
                        Table of cells before / after QC
num_cell_after_cor_filt_scExp
                        Number of cells before & after correlation
                        filtering
num_cell_before_cor_filt_scExp
                        Table of number of cells before correlation
                        filtering
num_cell_in_cluster_scExp
                        Number of cells in each cluster
num_cell_scExp          Table of cells
pca_irlba_for_sparseMatrix
                        Run sparse PCA using irlba SVD
peaks_to_bins           Transforms a peaks x cells count matrix into a
                        bins x cells count matrix.
plot_cluster_consensus_scExp
                        Plot cluster consensus
plot_coverage_BigWig    Coverage plot using Sushi
plot_differential_H1_scExp
                        Differential H1 distribution plot
plot_differential_summary_scExp
                        Differential summary barplot
plot_differential_volcano_scExp
                        Volcano plot of differential features
plot_distribution_scExp
                        Plotting distribution of signal
plot_gain_or_loss_barplots
                        Plot Gain or Loss of cytobands of the most
                        variables cytobands
plot_heatmap_scExp      Plot cell correlation heatmap with annotations
plot_inter_correlation_scExp
                        Violin plot of inter-correlation distribution
                        between one or multiple groups and one
                        reference group
plot_intra_correlation_scExp
                        Violin plot of intra-correlation distribution
plot_most_contributing_features
                        Plot Top/Bottom most contributing features to
                        PCA
plot_pie_most_contributing_chr
                        Pie chart of top contribution of chromosomes in
                        the 100 most contributing features to PCA #'
plot_reduced_dim_scExp
                        Plot reduced dimensions (PCA, TSNE, UMAP)
plot_reduced_dim_scExp_CNA
                        Plot UMAP colored by Gain or Loss of cytobands
preprocess_CPM          Preprocess scExp - Counts Per Million (CPM)
preprocess_RPKM         Preprocess scExp - Read per Kilobase Per
                        Million (RPKM)
preprocess_TFIDF        Preprocess scExp - TF-IDF
preprocess_TPM          Preprocess scExp - Transcripts per Million
                        (TPM)
preprocess_feature_size_only
                        Preprocess scExp - size only
raw_counts_to_sparse_matrix
                        Create a sparse count matrix from various
                        format of input data.
rawfile_ToBigWig        rawfile_ToBigWig : reads in BAM file and write
                        out BigWig coverage file, normalized and
                        smoothed
read_count_mat_with_separated_chr_start_end
                        Read a count matrix with three first columns
                        (chr,start,end)
read_sparse_matrix      Read in one or multiple sparse matrices (10X
                        format)
reduce_dim_batch_correction
                        Reduce dimension with batch corrections
reduce_dims_scExp       Reduce dimensions (PCA, TSNE, UMAP)
remove_chr_M_fun        Remove chromosome M from scExprownames
remove_non_canonical_fun
                        Remove non canonical chromosomes from scExp
results_enrichmentTest
                        Resutls of hypergeometric gene set enrichment
                        test
retrieve_top_bot_features_pca
                        Retrieve Top and Bot most contributing features
                        of PCA
run_pairwise_tests      Run pairwise tests
run_tsne_scExp          Run tsne on single cell experiment
scExp                   A SingleCellExperiment outputed by ChromSCape
separate_BAM_into_clusters
                        Separate BAM files into cell cluster BAM files
separator_count_mat     Determine Count matrix separator ("tab" or ",")
smoothBin               Smooth a vector of values with nb_bins left and
                        righ values
subsample_scExp         Subsample scExp
subset_bam_call_peaks   Peak calling on cell clusters
swapAltExp_sameColData
                        Swap main & alternative Experiments, with fixed
                        colData
table_enriched_genes_scExp
                        Creates table of enriched genes sets
warning_DA              Warning for differential_analysis_scExp
warning_filter_correlated_cell_scExp
                        warning_filter_correlated_cell_scExp
warning_plot_reduced_dim_scExp
                        A warning helper for plot_reduced_dim_scExp
warning_raw_counts_to_sparse_matrix
                        Warning for raw_counts_to_sparse_matrix
wrapper_Signac_FeatureMatrix
                        Wrapper around 'FeatureMatrix' function from
                        Signac Package
