An R client for BEDbase

bedbaser exposes the bedhost API and includes convenience functions for common tasks, such as to import a BED file by id into a GRanges object and a BEDset by its id into a GRangesList.

BEDbase(cache_path, quietly = FALSE)

getCache(x, cache_type = c("bedfiles", "bedsets"))

setCache(x, cache_path, quietly = TRUE)

Arguments

cache_path

character(1)

quietly

logical(1) (default TRUE) display messages

x

BEDbase() object

cache_type

character(1) bedfiles or bedsets

Value

BEDbase object

Details

BEDbase() creates a cache similar to that of the Geniml BBClient's cache.

The convenience functions are as follows

• bedbaser::BEDbase(): API service constructor

• bedbaser::getCache(): Retrieve cache

• bedbaser::setCache(): Set path to cache

• bedbaser::bb_stats(): Retrieve BEDbase statistics

• bedbaser::bb_example(): Retrieve an example BED file or BEDset

• bedbaser::bb_metadata(): Retrieve metadata for a BED file or BEDset

• bedbaser::bb_list_beds(): List all BED files

• bedbaser::bb_list_bedsets(): List all BEDsets

• bedbaser::bb_beds_in_bedset(): List BED files in BEDset

• bedbaser::bb_bed_text_search(): Search BED files by text

• bedbaser::bb_to_granges(): Create a GRanges object from a BED id

• bedbaser::bb_to_grangeslist(): Create a GRangesList from a BEDset id

• bedbaser::bb_save(): Save a BED file to a path.

Examples

bedbase <- BEDbase(cache_path = tempdir())
#> 125977 BED files available.
ex_bed <- bb_example(bedbase, "bed")
bb_metadata(bedbase, ex_bed$id)
#> $name
#> [1] "encode_10240"
#> 
#> $genome_alias
#> [1] "hg38"
#> 
#> $genome_digest
#> [1] "2230c535660fb4774114bfa966a62f823fdb6d21acf138d4"
#> 
#> $bed_compliance
#> [1] "bed6+3"
#> 
#> $data_format
#> [1] "encode_broadpeak"
#> 
#> $compliant_columns
#> [1] 6
#> 
#> $non_compliant_columns
#> [1] 3
#> 
#> $header
#> NULL
#> 
#> $id
#> [1] "afbdec2bd8ff7f22467a39d6146d1714"
#> 
#> $description
#> [1] "GM DNase-seq experiment on K562 (Blast phase chronic myelogenous leukemia, BCR-ABL1 positive cell line from pleural effusion)"
#> 
#> $submission_date
#> [1] "2025-04-28T23:15:53.132875Z"
#> 
#> $last_update_date
#> [1] "2025-07-18T20:52:00.968951Z"
#> 
#> $is_universe
#> [1] FALSE
#> 
#> $license_id
#> [1] "DUO:0000042"
#> 
#> $annotation
#> $annotation$species_name
#> [1] "Homo sapiens"
#> 
#> $annotation$species_id
#> [1] "9606"
#> 
#> $annotation$genotype
#> [1] ""
#> 
#> $annotation$phenotype
#> [1] ""
#> 
#> $annotation$description
#> [1] ""
#> 
#> $annotation$cell_type
#> [1] ""
#> 
#> $annotation$cell_line
#> [1] "K562"
#> 
#> $annotation$tissue
#> [1] ""
#> 
#> $annotation$library_source
#> [1] "genomic"
#> 
#> $annotation$assay
#> [1] "DNase-Hypersensitivity"
#> 
#> $annotation$antibody
#> [1] ""
#> 
#> $annotation$target
#> [1] ""
#> 
#> $annotation$treatment
#> [1] ""
#> 
#> $annotation$global_sample_id
#> $annotation$global_sample_id[[1]]
#> [1] "encode:ENCFF708QSW"
#> 
#> $annotation$global_sample_id[[2]]
#> [1] "geo:gsm2400267"
#> 
#> 
#> $annotation$global_experiment_id
#> $annotation$global_experiment_id[[1]]
#> [1] "encode"
#> 
#> $annotation$global_experiment_id[[2]]
#> [1] "geo:gse90287"
#> 
#> 
#> $annotation$original_file_name
#> [1] "GSM2400267_ENCFF708QSW_hotspots_GRCh38.bed.gz"
#> 
#> 
#> $processed
#> [1] TRUE
#> 
#> $stats
#> NULL
#> 
#> $plots
#> NULL
#> 
#> $files
#> NULL
#> 
#> $universe_metadata
#> NULL
#> 
#> $raw_metadata
#> NULL
#> 
#> $bedsets
#> list()
#>