Package index • BPCells

ATAC-seq Fragments

Fragment I/O

open_fragments_10x() write_fragments_10x(): Read/write a 10x fragments file

write_fragments_memory() write_fragments_dir() open_fragments_dir() write_fragments_hdf5() open_fragments_hdf5(): Read/write BPCells fragment objects

convert_to_fragments() as() as.data.frame(): Convert between BPCells fragments and R objects.

ATAC Analysis

qc_scATAC(): Calculate ArchR-compatible per-cell QC statistics

nucleosome_counts(): Count fragments by nucleosomal size

footprint(): Get footprints around a set of genomic coordinates

peak_matrix(): Calculate ranges x cells overlap matrix

tile_matrix(): Calculate ranges x cells tile overlap matrix

gene_score_weights_archr() gene_score_archr(): Calculate GeneActivityScores

call_peaks_macs(): Call peaks using MACS2/3

call_peaks_tile(): Call peaks from tiles

merge_peaks_iterative(): Merge peaks

write_insertion_bedgraph() write_insertion_bed(): Write insertion counts to bed/bedgraph file

Fragment Operations

shift_fragments(): Shift start or end coordinates

select_chromosomes(): Subset, translate, or reorder chromosome IDs

select_cells(): Subset, translate, or reorder cell IDs

merge_cells(): Merge cells into pseudobulks

subset_lengths(): Subset fragments by length

select_regions(): Subset fragments by genomic region

prefix_cell_names(): Add sample prefix to cell names

show(<IterableFragments>) cellNames() `cellNames<-`() chrNames() `chrNames<-`(): IterableFragments methods

fragments_identical(): Check if two fragments objects are identical

Genomic Range Calculations

genomic-ranges-like: Genomic range formats

order_ranges(): Get end-sorted ordering for genome ranges

range_distance_to_nearest(): Find signed distance to nearest genomic ranges

extend_ranges(): Extend genome ranges in a strand-aware fashion.

gene_score_tiles_archr(): Calculate gene-tile distances for ArchR gene activities

normalize_ranges(): Normalize an object representing genomic ranges

Matrix Operations (RNA + ATAC)

Matrix I/O

open_matrix_10x_hdf5() write_matrix_10x_hdf5(): Read/write a 10x feature matrix

open_matrix_anndata_hdf5() write_matrix_anndata_hdf5() write_matrix_anndata_hdf5_dense(): Read/write AnnData matrix

write_matrix_memory() write_matrix_dir() open_matrix_dir() write_matrix_hdf5() open_matrix_hdf5(): Read/write sparse matrices

import_matrix_market() import_matrix_market_10x(): Import MatrixMarket files

as() as.matrix(): Convert between BPCells matrix and R objects.

Matrix Operations

marker_features(): Test for marker features

matrix_stats(): Calculate matrix stats

svds(): Calculate svds

convert_matrix_type(): Convert the type of a matrix

transpose_storage_order(): Transpose the storage order for a matrix

sctransform_pearson(): SCTransform Pearson Residuals

min_scalar() min_by_row() min_by_col(): Elementwise minimum

add_rows() add_cols() multiply_rows() multiply_cols(): Broadcasting vector arithmetic

binarize(): Convert matrix elements to zeros and ones

all_matrix_inputs() `all_matrix_inputs<-`(): Get/set inputs to a matrix transform

checksum(): Calculate the MD5 checksum of an IterableMatrix

apply_by_row() apply_by_col(): Apply a function to summarize rows/cols

regress_out(): Regress out unwanted variation

matrix_type() storage_order() show(<IterableMatrix>) t(<IterableMatrix>) `%*%`(<IterableMatrix>,<matrix>) rowSums(<IterableMatrix>) colSums(<IterableMatrix>) rowMeans(<IterableMatrix>) colMeans(<IterableMatrix>) colVars() rowVars() rowMaxs() colMaxs() rowQuantiles() colQuantiles() log1p(<IterableMatrix>) log1p_slow() expm1(<IterableMatrix>) expm1_slow() `^`(<IterableMatrix>,<numeric>) `<`(<numeric>,<IterableMatrix>) `>`(<IterableMatrix>,<numeric>) `<=`(<numeric>,<IterableMatrix>) `>=`(<IterableMatrix>,<numeric>) round(<IterableMatrix>) `*`(<IterableMatrix>,<numeric>) `+`(<IterableMatrix>,<numeric>) `/`(<IterableMatrix>,<numeric>) `-`(<IterableMatrix>,<numeric>): IterableMatrix methods

pseudobulk_matrix(): Aggregate counts matrices by cell group or feature.

Reference Annotations

human_gene_mapping mouse_gene_mapping: Gene Symbol Mapping data

match_gene_symbol() canonical_gene_symbol(): Gene symbol matching

read_gtf() read_gencode_genes() read_gencode_transcripts(): Read GTF gene annotations

read_bed() read_encode_blacklist(): Read a bed file into a data frame

read_ucsc_chrom_sizes(): Read UCSC chromosome sizes

Clustering

cluster_cells_graph(): Cluster cell embeddings using a KNN graph-based algorithm

knn_hnsw() knn_annoy(): Get a knn object from reduced dimensions

cluster_graph_leiden() cluster_graph_louvain() cluster_graph_seurat(): Cluster an adjacency matrix

knn_to_graph() knn_to_snn_graph() knn_to_geodesic_graph(): K Nearest Neighbor (KNN) Graph

cluster_membership_matrix(): Convert grouping vector to sparse matrix

Plots

Single cell plots

plot_read_count_knee(): Knee plot of single cell read counts

plot_embedding(): Plot UMAP or embeddings

plot_dot(): Dotplot

plot_fragment_length(): Fragment size distribution

plot_tf_footprint(): Plot TF footprint

plot_tss_profile(): Plot TSS profile

plot_tss_scatter(): TSS Enrichment vs. Fragment Counts plot

Genomic track plots

trackplot_combine(): Combine track plots

trackplot_coverage(): Pseudobulk coverage trackplot

trackplot_gene(): Plot transcript models

trackplot_loop(): Plot loops

trackplot_genome_annotation(): Plot range-based annotation tracks (e.g. peaks)

trackplot_scalebar(): Plot scale bar

gene_region(): Find gene region

set_trackplot_label() set_trackplot_height() get_trackplot_height(): Adjust trackplot properties

Plotting utilities

discrete_palette() continuous_palette(): Color palettes

collect_features(): Collect features for plotting

rotate_x_labels(): Rotate ggplot x axis labels

Data

get_demo_mat() get_demo_frags() remove_demo_data() experimental: Retrieve BPCells demo data