Return all available BED files ranked by relevance to the keywords. Uses the bedhost API default of 10 records and an initial offset of 0.
bb_bed_text_search(
bedbase,
query,
genome = NULL,
assay = NULL,
limit = 10,
offset = 0
)tibble of results
bedbase <- BEDbase()
#> 128999 BED files available.
bb_bed_text_search(bedbase, "hg38")
#> # A tibble: 10 × 43
#> id payload.id payload.name payload.description payload.cell_line
#> <chr> <chr> <chr> <chr> <chr>
#> 1 6be4f1fb7464a8… 6be4f1fb7… ChIP_HL60_H… "" HL-60
#> 2 3986a74ae4f050… 3986a74ae… ChIP_HL60_H… "" HL-60
#> 3 5691d9009f9614… 5691d9009… ChIP_HL60_H… "" HL-60
#> 4 2334a9fc37fadf… 2334a9fc3… HCC38_H3K27… "" HCC38
#> 5 1b7fc14e60f8af… 1b7fc14e6… ChIP_HL60_H… "" HL-60
#> 6 df98019401d35a… df9801940… HL-60_H3K27… "" HL-60
#> 7 9f17013256fca6… 9f1701325… HT1376_DMSO… "" HT1376
#> 8 4353d91e0c7c6c… 4353d91e0… H3K27ac_ChI… "" 786-O
#> 9 fbee3b0091eaa2… fbee3b009… ChIP_HL60_S… "" HL-60
#> 10 95bc6dd2083d3a… 95bc6dd20… H3K27ac_ChI… "" 786-O
#> # ℹ 38 more variables: payload.cell_type <chr>, payload.tissue <chr>,
#> # payload.target <chr>, payload.treatment <chr>, payload.assay <chr>,
#> # payload.genome_alias <chr>, payload.species_name <chr>, score <chr>,
#> # metadata.name <chr>, metadata.genome_alias <chr>,
#> # metadata.bed_compliance <chr>, metadata.data_format <chr>,
#> # metadata.compliant_columns <chr>, metadata.non_compliant_columns <chr>,
#> # metadata.id <chr>, metadata.description <chr>, …