crisprScoreData can be installed from the Bioconductor
devel branch using the following commands in a fresh R session:
We first load the crisprScoreData package:
## Loading required package: ExperimentHub## Loading required package: BiocGenerics## Loading required package: generics##
## Attaching package: 'generics'## The following objects are masked from 'package:base':
##
## as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
## setequal, union##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:stats':
##
## IQR, mad, sd, var, xtabs## The following object is masked from 'package:utils':
##
## data## The following objects are masked from 'package:base':
##
## anyDuplicated, aperm, append, as.data.frame, basename, cbind,
## colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find,
## get, grep, grepl, is.unsorted, lapply, Map, mapply, match, mget,
## order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
## rbind, Reduce, rownames, sapply, saveRDS, scale, sequence, table,
## tapply, transform, unique, unsplit, which.max, which.min## Loading required package: AnnotationHub## Loading required package: BiocFileCache## Loading required package: dbplyrThis package contains several pre-trained models for different on-target activity prediction algorithms to be used in the package crisprScore.
We can access the file paths of the different pre-trained models directly with named functions:
## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## EH6123
## "/github/home/.cache/R/ExperimentHub/f0350e1281b_6166"## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## EH6124
## "/github/home/.cache/R/ExperimentHub/f035fb26731_6167"## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## EH6125
## "/github/home/.cache/R/ExperimentHub/f0353a7f6e3_6168"## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## EH6126
## "/github/home/.cache/R/ExperimentHub/f034c786b9d_6169"## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## EH6127
## "/github/home/.cache/R/ExperimentHub/f03538be4e9_6170"## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## EH6128
## "/github/home/.cache/R/ExperimentHub/f0344545af8_6171"Or we can access them using the ExperimentHub interface:
## ExperimentHub with 9 records
## # snapshotDate(): 2026-10-07
## # $dataprovider: Fudan University, UCSF, University of Washington, New York ...
## # $species: NA
## # $rdataclass: character
## # additional mcols(): taxonomyid, genome, description,
## # coordinate_1_based, maintainer, rdatadateadded, preparerclass, tags,
## # rdatapath, sourceurl, sourcetype
## # retrieve records with, e.g., 'object[["EH6123"]]'
##
## title
## EH6123 | DeepWt.hdf5
## EH6124 | DeepWt_T7.hdf5
## EH6125 | DeepWt_U6.hdf5
## EH6126 | esp_rnn_model.hdf5
## EH6127 | hf_rnn_model.hdf5
## EH6128 | Model_weights.pkl
## EH7304 | CRISPRa_model.pkl
## EH7305 | CRISPRi_model.pkl
## EH7356 | RFcombined.rds## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## loading from cache## EH6127
## "/github/home/.cache/R/ExperimentHub/f03538be4e9_6170"For details on the source of these files, and on their construction
see ?crisprScoreData and the scripts:
inst/scripts/make-metadata.Rinst/scripts/make-data.Rmd## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 26.04.1 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] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] crisprScoreData_1.17.0 ExperimentHub_3.3.2 AnnotationHub_4.3.2
## [4] BiocFileCache_3.3.0 dbplyr_2.6.0 BiocGenerics_0.59.12
## [7] generics_0.1.4 BiocStyle_2.41.0
##
## loaded via a namespace (and not attached):
## [1] rappdirs_0.3.4 sass_0.4.10 BiocVersion_3.24.0
## [4] RSQLite_3.53.3 digest_0.6.39 magrittr_2.0.5
## [7] evaluate_1.0.5 fastmap_1.2.0 blob_1.3.0
## [10] jsonlite_2.0.0 AnnotationDbi_1.75.2 DBI_1.3.0
## [13] BiocManager_1.30.27 httr_1.4.9 purrr_1.2.2
## [16] Biostrings_2.81.9 httr2_1.3.0 jquerylib_0.1.4
## [19] cli_3.6.6 crayon_1.5.3 rlang_1.3.0
## [22] XVector_0.53.0 Biobase_2.73.2 bit64_4.8.6
## [25] withr_3.0.3 cachem_1.1.0 yaml_2.3.12
## [28] BiocBaseUtils_1.15.1 otel_0.2.0 tools_4.6.1
## [31] memoise_2.0.1 dplyr_1.2.1 filelock_1.0.3
## [34] curl_8.0.0 png_0.1-9 buildtools_1.0.0
## [37] vctrs_0.7.3 R6_2.6.1 stats4_4.6.1
## [40] lifecycle_1.0.5 Seqinfo_1.3.2 KEGGREST_1.53.6
## [43] S4Vectors_0.51.10 IRanges_2.47.5 bit_4.6.0
## [46] pkgconfig_2.0.3 pillar_1.11.1 bslib_0.12.0
## [49] glue_1.8.1 xfun_0.61 tibble_3.3.1
## [52] tidyselect_1.2.1 sys_3.4.3 knitr_1.52
## [55] htmltools_0.5.9 rmarkdown_2.32 maketools_1.3.2
## [58] compiler_4.6.1