Function reference • mcATAC

All functions

ATAC-class ATAC: ATAC objects

ATACPeaks-class ATACPeaks: ATACPeaks objects

McPeaks-class McPeaks ScPeaks-class ScPeaks: McPeaks

ATACTracks-class ATACTracks: ATACTracks objects

McTracks-class McTracks: McTracks

PeakIntervals(): Construct a PeakIntervals object from misha intervals

ScCounts-class ScCounts: ScCounts object

McCounts-class McCounts: McCounts object

add_mc_metadata(): Add per-metacell metadata to an McPeaks object

add_mc_rna(): Add per-metacell gene expression data to an McPeaks object

annotate_intervals(): Annotate an intervals set

annotate_peaks(): Annotate ATAC peaks

atac_ignore_cells(): Remove cells

atac_ignore_peaks(): Set ignored (i.e. blacklisted) peaks

bam_file_chromosomes(): Get chromosomes from a bam file

calc_prom_rna_cor(): Calculate the cross-correlation between promoter accessibility and RNA expression

calculate_d_stats(): Calculate Kolmogorov-Smirnov D statistics between two interval sets with motif energies

call_peaks(): Call peaks from ATAC marginals track

canonize_peaks(): Generate a set of non-overlapping peaks from a set of intervals

check_dependencies(): Test if mcATAC has the required dependencies

clear_cache(): Clear the ATAC track matrix cache

create_bundle(): Create a bundle for the shiny app in order to run it with shiny server

download_pbmc_example_data(): Download example data from 10x

export_atac_clust_misha(): Generate a misha track for each atac metacell cluster

export_atac_clust_ucsc(): Generate a ucsc genome browser file for each metacell cluster

export_to_h5ad(): Write a McPeaks or ScPeaks object to an h5ad file

filter_features(): Filter features by summary statistics

find_blacklist_overlaps(): Find overlaps with ENCODE blacklists

gen_atac_mc_clust(): Cluster metacells based on atac profiles using the k-means algorithm

gen_atac_peak_clust(): Cluster atac peaks based on atac distributions

gen_promoter_features(): Select only peaks that are close to a gene promoter

gen_random_genome_peak_motif_matrix(): Generate random genome motif PSSM matrix

generate_motif_pssm_matrix(): Generate peak-motif matrix

generate_pheatmap_annotation(): Function to generate generic pheatmap annotation

get_available_pssms(): Function for validating pssm_path and getting all/selected PSSM datasets and tracks from path/gdb

get_gene_promoter(): Get an intervals set of a gene promoter.

get_genes_atac_fp(): Return a relative fold change matrix of ATAC peaks for a list of genes

get_peak_coverage_stats(): Calculate coverage statistics of the peaks

get_promoter_peaks(): Get the names of the peaks close to a gene promoter

get_quantile_cov_thresh(): Calculate the threshold for calling peaks

get_rna_egc(): Get the normalized RNA expression matrix (egc) from a McPeaks object

get_rna_fp(): Get enrichment of normalized counts of gene expression over the median

get_rna_marker_matrix(): Get enrichment matrix for marker genes

get_rna_markers(): Calculate gene markers of metacells gene expression

get_track_total_coverage(): Return the total coverage of a track

gintervals.extend_left(): Extend the coordinates of an intervals set to the left.

gintervals.extend_right(): Extend the coordinates of an intervals set to the right.

gintervals.shift_left(): Shift the coordinates of an intervals set to the left.

gintervals.shift_right(): Shift the coordinates of an intervals set to the right.

gintervals.zoom_in(): Zoom-in for an intervals set.

gintervals.zoom_out(): Zoom-out for an intervals set.

has_cell_type(): Does the McPeaks object contain per-metacell cell type annotation

has_cell_type_colors(): Does the McPeaks object contain cell type color annotation

has_rna(): Does the McPeaks object contain per-metacell gene expression data?

identify_dynamic_peaks(): Find dynamic peaks in McPeaks matrix

import_atac_marginal(): Import marginal of ATAC counts to a misha track

import_from_10x(): Create an ScPeaks object from 10x directory

import_from_h5ad(): Create an ScPeaks,McPeaks object from an h5ad file

import_from_matrix(): Create an ScPeaks,McPeaks object from matrix and peaks

infer_track_order(): Infer order of metacell track names by metacell number

initialize(<McPeaks>): Construct a new McPeaks object

initialize(<ScPeaks>): Construct a new ScPeaks object

mc_hclust_rna(): Hierarchical clustering of metacells using RNA markers

mc_order(): Order the metacells in an MC object

mc_order_by_rna(): Order metacells by RNA marker clustering

mcc_extract_to_df(): Extract McCounts to a tidy data frame

mcc_marginal() scc_marginal(): Return the total coverage of each non-zero coordinate in an ScCounts/McCounts object

mcc_metacell_total_cov(): Return the total coverage of each metacell in an McCounts object

mcc_normalize_metacells(): Normalize each metacell in a McCounts object by its total counts

mcc_read(): Read an McCounts object from a directory

mcc_to_marginal_track() scc_to_marginal_track(): Create a track with smoothed marginal counts from an ScCounts/McCounts object

mcc_to_mcatac(): Create an McPeaks object from an McCounts object

mcc_to_tracks(): Create a misha track for each metacell in a McCounts object

mct_create(): Create an McTracks object

mct_diff_access_on_hc(): Return a mask matrix with differential cluster accessibility (DCA)

mct_get_mat(): Get an ATAC matrix from a McTracks object

mct_ls_cached_regions(): List the cached regions of an McTracks object

mct_plot_region(): Plot a genomic region

mct_to_mcatac(): Create an McPeaks object from McTracks object

name_enhancers(): Name ATAC peaks from TAD names

normalize_egc(): Normalize McPeaks data using marginal coverage

normalize_marginal(): Normalize Marginal Track

order_tracks(): Order metacell tracks by metacell number

peak_names(): Return the names of PeakIntervals

plot_atac_atac_cor(): Plot a correlation matrix of ATAC metacells

plot_atac_peak_map(): Plot normalized accessibility of peaks over metacells, ordered by clustering

plot_atac_rna(): Plot a scatter of gene expression vs an atac profile

plot_atac_rna_cor(): Plot a cross-correlation matrix between RNA metacells and ATAC metacell scores

plot_atac_rna_markers(): Plot RNA and ATAC marker matrix side by side

plot_marginal_coverage(): Plot marginal coverage of an interval

plot_motif_logo(): Plot LOGO of a motif

plot_peak_coverage_density(): Plot the coverage density of the peaks

plot_peak_coverage_distribution(): Plot the coverage distribution of the peaks

plot_peak_length_distribution(): Plot the distribution of the peak length

plot_peak_max_cov_distribution(): Plot the maximal per-cell coverage distribution of the peaks

plot_region_mat(): Plot a genomic region given a matrix

plot_rna_markers(): Plot a heatmap of marker genes fold change over metacells given an McPeaks object

plot_rna_markers_mat(): Plot a heatmap of marker genes fold change over metacells

plot_tracks_at_locus(): Plot metacell tracks around locus

project_atac_on_mc() project_atac_on_mc_from_metacell1() project_atac_on_mc_from_h5ad(): Given metacells (usually from RNA data), project ATAC counts to get a McPeaks object

rna_atac_cor_knn(): Match every gene with the k ATAC peaks most correlated to it

run_app(): Run a shiny app for viewing the MCT object

save_pheatmap(): Function to save pheatmaps to disk while showing them on screen

scc_change_names(): Change the cell names of a ScCounts object

scc_extract(): Extract summary statistics per cell for a set of intervals

scc_from_10x() write_sc_counts_from_10x(): Write single cell counts from 10x 'outs' directory

write_sc_counts_from_bam() scc_from_bam(): Write single cell counts from an indexed bam file

scc_from_fragments() write_sc_counts_from_fragments(): Write single cell counts from a 10x fragments file

scc_read(): Read an ScCounts object from a directory

scc_to_mcc() scc_project_on_mc(): Given metacells (usually from RNA data), project ATAC counts to get a McCounts object

scc_to_mcc_multi_batch(): Given metacells (usually from RNA data), project ATAC counts from multiple batches to get a McCounts object

scc_to_peaks(): Create an ScPeaks object from an ScCounts object

scc_write() mcc_write(): Write a counts object to a file

set_parallel(): Set parallel threads

split_long_peaks(): Split long peaks into smaller peaks

subset_peak_clusters(): Subset McPeaks by certain clusters

subset_peaks(): Subset peaks of an McPeaks object

temp_track_name(): Get a temporary track name

write_sparse_matrix_from_bam(): Write a sparse-matrix file from an indexed bam file