dbSequence stores genomic data in DuckDB, enabling analysis of datasets larger than available memory. Data stays in the database—R operates on lazy references. Compared with general out-of-memory tools in the CRAN High-Performance Computing Task View and Delayed* Bioconductor packages, dbSequence focuses on database-backed genomic interval ingestion and overlap queries.
| Format | Function | BiocIO Class |
|---|---|---|
| BED | read_bed() |
BEDFile |
| VCF | read_vcf() |
VcfFile |
| GFF/GTF | read_gff() |
GFFFile |
| BAM | read_bam() |
BamFile |
library(dbSequence)
bed_file <- system.file("extdata", "example.bed", package = "dbSequence")
# Import a BED file
db_seq <- read_bed(bed_file)
# Data stays in DuckDB - this is a lazy reference
db_seq
#> # A query: ?? x 6
#> # Database: DuckDB 1.5.4 [unknown@Linux 6.17.0-1018-azure:R 4.6.1/:memory:]
#> seqnames start end name score strand
#> <chr> <int> <int> <chr> <dbl> <chr>
#> 1 chr1 101 200 feature1 500 +
#> 2 chr1 301 400 feature2 750 -
#> 3 chr2 151 250 feature3 600 +
#> 4 chr2 501 600 feature4 800 -
#> 5 chr3 1001 1100 feature5 650 +
#> 6 chr3 2001 2100 feature6 900 +
#> 7 chr4 501 700 feature7 550 -
#> 8 chr4 1501 1600 feature8 720 +
#> 9 chr5 801 900 feature9 680 +
#> 10 chr5 1201 1300 feature10 590 -For more control, use the BiocIO import() function:
The key feature: data never loads into R memory.
# This does NOT load data
db_seq <- read_bed(bed_file)
# Still no data in memory - just adds a filter condition
region <- GenomicRanges::GRanges("chr1:100-500")
filtered <- filter_by_overlaps(db_seq, region)
# Data only loads when you explicitly collect
result <- as_granges(filtered) # NOW data enters RStore multiple datasets in one database:
db <- DuckDBFile(tempfile(fileext = ".duckdb"))
gff_file <- system.file("extdata", "example.gff3", package = "dbSequence")
# Import different files to same database
peaks <- import(BEDFile(bed_file), dest = db, table_name = "peaks")
genes <- import(GFFFile(gff_file), dest = db, table_name = "genes")dbSequence manages connections automatically, but for long sessions:
sessionInfo()
#> R version 4.6.1 (2026-06-24)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 26.04 LTS
#>
#> Matrix products: default
#> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.32.so; LAPACK version 3.12.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
#> [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
#> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
#> [9] LC_ADDRESS=C LC_TELEPHONE=C
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods
#> [8] base
#>
#> other attached packages:
#> [1] rtracklayer_1.73.0 GenomicRanges_1.65.1 Seqinfo_1.3.0
#> [4] IRanges_2.47.2 S4Vectors_0.51.5 BiocGenerics_0.59.10
#> [7] generics_0.1.4 BiocIO_1.23.3 dbSequence_0.99.1
#> [10] BiocStyle_2.41.0
#>
#> loaded via a namespace (and not attached):
#> [1] KEGGREST_1.53.5 SummarizedExperiment_1.43.0
#> [3] rjson_0.2.23 xfun_0.59
#> [5] bslib_0.11.0 Biobase_2.73.1
#> [7] lattice_0.22-9 vctrs_0.7.3
#> [9] tools_4.6.1 bitops_1.0-9
#> [11] curl_7.1.0 parallel_4.6.1
#> [13] tibble_3.3.1 AnnotationDbi_1.75.0
#> [15] RSQLite_3.53.3 blob_1.3.0
#> [17] pkgconfig_2.0.3 BiocBaseUtils_1.15.1
#> [19] Matrix_1.7-5 BSgenome_1.81.0
#> [21] dbplyr_2.6.0 cigarillo_1.3.0
#> [23] rscontract_0.1.2 lifecycle_1.0.5
#> [25] compiler_4.6.1 Rsamtools_2.29.0
#> [27] Biostrings_2.81.5 codetools_0.2-20
#> [29] htmltools_0.5.9 sys_3.4.3
#> [31] buildtools_1.0.0 sass_0.4.10
#> [33] RCurl_1.98-1.19 yaml_2.3.12
#> [35] pillar_1.11.1 crayon_1.5.3
#> [37] jquerylib_0.1.4 BiocParallel_1.47.0
#> [39] DelayedArray_0.39.3 cachem_1.1.0
#> [41] connections_0.2.1 abind_1.4-8
#> [43] tidyselect_1.2.1 digest_0.6.39
#> [45] duckdb_1.5.4.2 dplyr_1.2.1
#> [47] purrr_1.2.2 restfulr_0.0.17
#> [49] VariantAnnotation_1.59.0 pins_1.4.2
#> [51] maketools_1.3.2 fastmap_1.2.0
#> [53] grid_4.6.1 cli_3.6.6
#> [55] SparseArray_1.13.2 magrittr_2.0.5
#> [57] S4Arrays_1.13.0 GenomicFeatures_1.65.0
#> [59] utf8_1.2.6 XML_3.99-0.23
#> [61] withr_3.0.3 bit64_4.8.2
#> [63] rmarkdown_2.31 XVector_0.53.0
#> [65] httr_1.4.8 matrixStats_1.5.0
#> [67] bit_4.6.0 otel_0.2.0
#> [69] png_0.1-9 dbProject_0.1.1
#> [71] memoise_2.0.1 evaluate_1.0.5
#> [73] knitr_1.51 rlang_1.3.0
#> [75] glue_1.8.1 DBI_1.3.0
#> [77] BiocManager_1.30.27 jsonlite_2.0.0
#> [79] R6_2.6.1 GenomicAlignments_1.49.1
#> [81] MatrixGenerics_1.25.0