JASPAR (https://testjaspar.uio.no/) is a widely-used open-access database presenting manually curated high-quality and non-redundant DNA-binding profiles for transcription factors (TFs) across taxa. In this 10th release and 20th-anniversary update, the CORE collection has expanded with 329 new profiles. We updated three existing profiles and provided orthogonal support for 72 profiles from the previous release’s UNVALIDATED collection. Altogether, the JASPAR 2024 update provides a 20% increase in CORE profiles from the previous release. A trimming algorithm enhanced profiles by removing low information content flanking base pairs, which were likely uninformative (within the capacity of the PFM models) for TFBS predictions and modelling TF-DNA interactions. This release includes enhanced metadata, featuring a refined classification for plant TFs’ structural DNA-binding domains. The new JASPAR collections prompt updates to the genomic tracks of predicted TF-binding sites in 8 organisms, with human and mouse tracks available as native tracks in the UCSC Genome browser. All data are available through the JASPAR web interface and programmatically through its API and the updated Bioconductor and pyJASPAR packages. Finally, a new TFBS extraction tool enables users to retrieve predicted JASPAR TFBSs intersecting their genomic regions of interest.
You can easily access data in JASPAR using the RSQLite package as shown:
library(JASPAR2024)
#> Loading required package: BiocFileCache
#> Loading required package: dbplyr
library(RSQLite)
JASPAR2024 <- JASPAR2024()
#> adding rname 'https://testjaspar.uio.no/download/database/JASPAR2024.sqlite'
JASPARConnect <- RSQLite::dbConnect(RSQLite::SQLite(), db(JASPAR2024))
RSQLite::dbGetQuery(JASPARConnect, 'SELECT * FROM MATRIX LIMIT 5')
#> ID COLLECTION BASE_ID VERSION NAME
#> 1 9229 CORE MA0001 1 AGL3
#> 2 9230 CORE MA0002 1 RUNX1
#> 3 9231 CORE MA0003 1 TFAP2A
#> 4 9232 CORE MA0004 1 Arnt
#> 5 9233 CORE MA0005 1 AG
dbDisconnect(JASPARConnect)Here is the output of sessionInfo() on the system on which this document was compiled:
#> R version 4.3.1 (2023-06-16)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 22.04.3 LTS
#>
#> Matrix products: default
#> BLAS: /home/biocbuild/bbs-3.18-bioc/R/lib/libRblas.so
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_GB LC_COLLATE=C
#> [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: America/New_York
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] RSQLite_2.3.1 JASPAR2024_0.99.6 BiocFileCache_2.9.1
#> [4] dbplyr_2.3.4 BiocStyle_2.29.2
#>
#> loaded via a namespace (and not attached):
#> [1] bit_4.0.5 jsonlite_1.8.7 dplyr_1.1.3
#> [4] compiler_4.3.1 BiocManager_1.30.22 filelock_1.0.2
#> [7] tidyselect_1.2.0 blob_1.2.4 jquerylib_0.1.4
#> [10] yaml_2.3.7 fastmap_1.1.1 R6_2.5.1
#> [13] generics_0.1.3 curl_5.1.0 knitr_1.44
#> [16] tibble_3.2.1 bookdown_0.36 DBI_1.1.3
#> [19] bslib_0.5.1 pillar_1.9.0 rlang_1.1.1
#> [22] utf8_1.2.3 cachem_1.0.8 xfun_0.40
#> [25] sass_0.4.7 bit64_4.0.5 memoise_2.0.1
#> [28] cli_3.6.1 withr_2.5.1 magrittr_2.0.3
#> [31] digest_0.6.33 lifecycle_1.0.3 vctrs_0.6.4
#> [34] evaluate_0.22 glue_1.6.2 fansi_1.0.5
#> [37] purrr_1.0.2 httr_1.4.7 rmarkdown_2.25
#> [40] tools_4.3.1 pkgconfig_2.0.3 htmltools_0.5.6.1