We first load the crisprScoreData package:
library(crisprScoreData)## Loading required package: ExperimentHub## Loading required package: BiocGenerics##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:stats':
##
## IQR, mad, sd, var, xtabs## The following objects are masked from 'package:base':
##
## Filter, Find, Map, Position, Reduce, anyDuplicated, append,
## as.data.frame, basename, cbind, colnames, dirname, do.call,
## duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
## lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
## pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
## tapply, union, unique, unsplit, which.max, which.min## Loading required package: AnnotationHub## Loading required package: BiocFileCache## Loading required package: dbplyr## snapshotDate(): 2022-04-19This 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:
# For DeepHF model:
DeepWt.hdf5()## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## loading from cache## EH6123
## "/home/biocbuild/.cache/R/ExperimentHub/3f58f85fb6e05d_6166"DeepWt_T7.hdf5()## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation
## loading from cache## EH6124
## "/home/biocbuild/.cache/R/ExperimentHub/9eb5947ce61a3_6167"DeepWt_U6.hdf5()## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation
## loading from cache## EH6125
## "/home/biocbuild/.cache/R/ExperimentHub/9eb591fe4d493_6168"esp_rnn_model.hdf5()## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation
## loading from cache## EH6126
## "/home/biocbuild/.cache/R/ExperimentHub/9eb5937f2dab_6169"hf_rnn_model.hdf5()## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation
## loading from cache## EH6127
## "/home/biocbuild/.cache/R/ExperimentHub/9eb59a6d9ee1_6170"# For Lindel model:
Model_weights.pkl()## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation
## loading from cache## EH6128
## "/home/biocbuild/.cache/R/ExperimentHub/a7620134cdfc1_6171"Or we can access them using the ExperimentHub interface:
eh <- ExperimentHub()## snapshotDate(): 2022-04-19query(eh, "crisprScoreData")## ExperimentHub with 9 records
## # snapshotDate(): 2022-04-19
## # $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.rdseh[["EH6127"]]## see ?crisprScoreData and browseVignettes('crisprScoreData') for documentation## loading from cache## EH6127
## "/home/biocbuild/.cache/R/ExperimentHub/9eb59a6d9ee1_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.RmdsessionInfo()## R version 4.2.0 RC (2022-04-19 r82224)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.15-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.15-bioc/R/lib/libRlapack.so
##
## 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
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] crisprScoreData_1.0.0 ExperimentHub_2.4.0 AnnotationHub_3.4.0
## [4] BiocFileCache_2.4.0 dbplyr_2.1.1 BiocGenerics_0.42.0
## [7] BiocStyle_2.24.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.8.3 png_0.1-7
## [3] Biostrings_2.64.0 assertthat_0.2.1
## [5] digest_0.6.29 utf8_1.2.2
## [7] mime_0.12 R6_2.5.1
## [9] GenomeInfoDb_1.32.0 stats4_4.2.0
## [11] RSQLite_2.2.12 evaluate_0.15
## [13] httr_1.4.2 pillar_1.7.0
## [15] zlibbioc_1.42.0 rlang_1.0.2
## [17] curl_4.3.2 jquerylib_0.1.4
## [19] blob_1.2.3 S4Vectors_0.34.0
## [21] rmarkdown_2.14 stringr_1.4.0
## [23] RCurl_1.98-1.6 bit_4.0.4
## [25] shiny_1.7.1 compiler_4.2.0
## [27] httpuv_1.6.5 xfun_0.30
## [29] pkgconfig_2.0.3 htmltools_0.5.2
## [31] tidyselect_1.1.2 KEGGREST_1.36.0
## [33] GenomeInfoDbData_1.2.8 tibble_3.1.6
## [35] interactiveDisplayBase_1.34.0 bookdown_0.26
## [37] IRanges_2.30.0 fansi_1.0.3
## [39] withr_2.5.0 crayon_1.5.1
## [41] dplyr_1.0.8 later_1.3.0
## [43] bitops_1.0-7 rappdirs_0.3.3
## [45] jsonlite_1.8.0 xtable_1.8-4
## [47] lifecycle_1.0.1 DBI_1.1.2
## [49] magrittr_2.0.3 cli_3.3.0
## [51] stringi_1.7.6 cachem_1.0.6
## [53] XVector_0.36.0 promises_1.2.0.1
## [55] bslib_0.3.1 ellipsis_0.3.2
## [57] filelock_1.0.2 generics_0.1.2
## [59] vctrs_0.4.1 tools_4.2.0
## [61] bit64_4.0.5 Biobase_2.56.0
## [63] glue_1.6.2 purrr_0.3.4
## [65] BiocVersion_3.15.2 fastmap_1.1.0
## [67] yaml_2.3.5 AnnotationDbi_1.58.0
## [69] BiocManager_1.30.17 memoise_2.0.1
## [71] knitr_1.39 sass_0.4.1