# Analysis of single-cell epigenomics datasets with a Shiny App

## Documentation for package ‘ChromSCape’ version 1.0.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

annotation_from_merged_peaks | Find nearest peaks of each gene and return refined annotation
annotToCol2 | annotToCol2
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
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
CompareedgeRGLM | Creates a summary table with the number of genes under- or overexpressed in each group and outputs several graphical representations
CompareWilcox | CompareWilcox
consensus_clustering_scExp | Wrapper to apply ConsensusClusterPlus to scExp object
correlation_and_hierarchical_clust_scExp | Correlation and hierarchical clustering
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
DA_one_vs_rest_fun | Differential Analysis in 'One vs Rest' mode
DA_pairwise | Run differential analysis in Pairwise mode
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
generate_count_matrix | Generate count matrix
generate_feature_names | Generate feature names
gene_set_enrichment_analysis_scExp | Runs Gene Set Enrichment Analysis on genes associated with differential features
get_color_dataframe_from_input | Get color dataframe from shiny::colorInput
get_genomic_coordinates | Get SingleCellExperiment's genomic coordinates
gg_fill_hue | gg_fill_hue
groupMat | groupMat
H1proportion | H1proportion
has_genomic_coordinates | Does SingleCellExperiment has genomic coordinates in features ?
hclustAnnotHeatmapPlot | hclustAnnotHeatmapPlot
hg38.chromosomes | Data.frame of chromosome length - hg38
hg38.GeneTSS | Data.frame of gene TSS - 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
launchApp | Launch ChromSCape
load_MSIGdb | Load and format MSIGdb pathways using msigdbr package
merge_MACS2_peaks | Merge peak files from MACS2 peak caller
mm10.chromosomes | Data.frame of chromosome length - mm10
mm10.GeneTSS | Data.frame of gene TSS - mm10
normalize_scExp | Normalize counts
num_cell_after_cor_filt_scExp | Number of cells before & after correlation filtering
num_cell_after_QC_filt_scExp | Table of cells before / after QC
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_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_heatmap_scExp | Plot cell correlation heatmap with annotations
plot_reduced_dim_scExp | Plot reduced dimensions (PCA, TSNE, UMAP)
preprocess_CPM | Preprocess scExp - Counts Per Million (CPM)
preprocess_feature_size_only | Preprocess scExp - size only
preprocess_RPKM | Preprocess scExp - Read per Kilobase Per Million (RPKM)
preprocess_TPM | Preprocess scExp - Transcripts per Million (TPM)
raw_counts_to_feature_count_files | Create a sparse count matrix from various format of input data.
read_count_mat_with_separated_chr_start_end | Read a count matrix with three first columns (chr,start,end)
reduce_dims_scExp | Reduce dimensions (PCA, TSNE, UMAP)
reduce_dim_batch_correction | Reduce dimension with batch corrections
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
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 ",")
subsample_scExp | Subsample scExp
subset_bam_call_peaks | Peak calling on cell clusters
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_feature_count_files | Warning for _raw_counts_to_feature_count_files