Function reference • stream

All functions
`create_rna_atac()`	Simulate a jointly profiled scRNA-seq and scATAC-seq dataset in which several enhancer regulons (eRegulons) are contained.
`enrich_genes()`	Perform enrichment analysis for eRegulon genes against gene ontology (GO) terms and KEGG pathways
`get_coverage_plot()`	Generate coverage plot within an interval across different cell types
`get_cts_en_GRNs()`	Predict cell-type-specific enhancer-driven gene regulatory networks (eGRNs)
`get_cts_en_regs()`	Identify cell-type-specific enhancer regulons (eRegulons)
`intersect_enhancer_gene_relations()`	Calculate the precision, recall, and f-scores of overlaps between two `GRanges` objects indicating enhancer-gene relations.
`intersect_enhancer_gene_relations_in_batch()`	Calculate the precision, recall, and f-scores of the overlaps between two lists of `GRanges` objects indicating enhancer-gene relations
`intersect_peaks()`	Calculate the p-values of overlaps between two `GRanges` objects
`intersect_peaks_in_batch()`	Calculate the p-values of overlaps between two lists of `GRanges` objects
`plot_dotplot_heatmap()`	Get the dotplot-heatmap for cell-type-specific enhancer regulons (eRegulons)
`plot_stats_genes_and_enhs()`	Generate multiple histograms for : The number of enhancers linked to each gene The rank of enhancers linked to each gene
`prepare_coverage_plot()`	Prepare TF-enhancer-gene relations to generate coverage plots
`run_stream()`	Identify enhancer regulons (eRegulons) from jointly profiled scRNA-seq and scATAC-seq data

Reference