- Overview
- Installation
- Datasets
- TxDb datasets
- TSS datasets
- mRNA datasets
- Repeats datasets
- Canonical transcripts
- Pfam domains
- License
- Reproducibility
Authors: Jean-Philippe Fortin, Luke Hoberecht
The crisprDesignData package provides ready-to-use annotation data
needed needed for the crisprVerse
ecosystem, for both human and human. Visit our crisprVerse tutorial
page to learn how the data
are used for performing CRISPR gRNA design.
This package is supported for macOS, Linux and Windows machines. It was developed and tested on R version 4.2.1.
crisprDesignData can be installed by typing the following commands
inside of an R session:
install.packages("devtools")
devtools::install_github("crisprVerse/crisprDesignData")crisprDesignData can be loaded into an R session in the usual way:
library(crisprDesignData)| Object name | Object class | Version | Description |
|---|---|---|---|
txdb_human |
GRangesList |
Release 104 | Ensembl gene model for human (hg38/GRCh38) |
txdb_mouse |
GRangesList |
Release 102 | Ensembl gene model for mouse (mm10/GRCm38) |
tss_human |
GRanges |
Release 104 | Ensembl-based TSS coordinates for human (hg38/GRCh38) |
tss_mouse |
GRanges |
Release 102 | Ensembl-based TSS coordinates for human (mm10/GRCm38) |
mrnasHuman |
DNAStringSet |
Release 104 | Ensembl-based mRNA nucleotide sequences for human (hg38/GRCh38) |
mrnasMouse |
DNAStringSet |
Release 102 | Ensembl-based mRNA nucleotide sequences for mouse (mm10/GRCm38) |
gr.repeats.hg38 |
GRanges |
RepeatMasker data from UCSC genome browser (hg38/GRCh38) | |
gr.repeats.mm10 |
GRanges |
RepeatMasker data from UCSC genome browser (mm10/GRCm38) | |
canonicalHuman |
data.frame |
Release 104 | Canonical Ensembl transcripts for human |
canonicalMouse |
data.frame |
Release 102 | Canonical Ensembl transcripts for mouse |
pfamTableHuman |
DataFrame |
Release 104 | Pfam domains for human Ensembl transcripts |
pfamTableMousen |
DataFrame |
Release 102 | Pfam domains for mouse Ensembl transcripts |
The txdb_human and txdb_mouse objects are GRangesList representing
gene models for human and mouse, respectively, from Ensembl. They were
constructed using the function getTxDb in crisprDesign. See the
script generateTxDbData.Rin the inst folder to see how to generate
such data for other organisms (internet connection needed).
Let’s look at the txdb_human object. We first load the data:
data(txdb_human, package="crisprDesignData")We can look at metadata information about the gene model by using the
metadata function from the S4Vectors package:
head(S4Vectors::metadata(txdb_human))## name value
## 1 Db type TxDb
## 2 Supporting package GenomicFeatures
## 3 Data source Ensembl
## 4 Organism Homo sapiens
## 5 Ensembl release 104
## 6 Ensembl database homo_sapiens_core_104_38
The object is a GRangesList with 7 elements that contain genomic
coordinates for different levels of the gene model:
names(txdb_human)## [1] "transcripts" "exons" "cds" "fiveUTRs" "threeUTRs"
## [6] "introns" "tss"
As an example, let’s look at the GRanges containing genomic
coordinates for all exons represented in the gene model:
txdb_human$exons## GRanges object with 796644 ranges and 14 metadata columns:
## seqnames ranges strand | tx_id gene_id
## <Rle> <IRanges> <Rle> | <character> <character>
## chr1 11869-12227 + | ENST00000456328 ENSG00000223972
## chr1 12613-12721 + | ENST00000456328 ENSG00000223972
## chr1 13221-14409 + | ENST00000456328 ENSG00000223972
## chr1 12010-12057 + | ENST00000450305 ENSG00000223972
## chr1 12179-12227 + | ENST00000450305 ENSG00000223972
## . ... ... ... . ... ...
## chrM 5826-5891 - | ENST00000387409 ENSG00000210144
## chrM 7446-7514 - | ENST00000387416 ENSG00000210151
## chrM 14149-14673 - | ENST00000361681 ENSG00000198695
## chrM 14674-14742 - | ENST00000387459 ENSG00000210194
## chrM 15956-16023 - | ENST00000387461 ENSG00000210196
## protein_id tx_type gene_symbol exon_id
## <character> <character> <character> <character>
## <NA> processed_transcript DDX11L1 ENSE00002234944
## <NA> processed_transcript DDX11L1 ENSE00003582793
## <NA> processed_transcript DDX11L1 ENSE00002312635
## <NA> transcribed_unproces.. DDX11L1 ENSE00001948541
## <NA> transcribed_unproces.. DDX11L1 ENSE00001671638
## . ... ... ... ...
## <NA> Mt_tRNA MT-TY ENSE00001544488
## <NA> Mt_tRNA MT-TS1 ENSE00001544487
## ENSP00000354665 protein_coding MT-ND6 ENSE00001434974
## <NA> Mt_tRNA MT-TE ENSE00001544476
## <NA> Mt_tRNA MT-TP ENSE00001544473
## exon_rank cds_start cds_end tx_start tx_end cds_len exon_start
## <integer> <integer> <integer> <integer> <integer> <integer> <integer>
## 1 <NA> <NA> 11869 14409 0 <NA>
## 2 <NA> <NA> 11869 14409 0 <NA>
## 3 <NA> <NA> 11869 14409 0 <NA>
## 1 <NA> <NA> 12010 13670 0 <NA>
## 2 <NA> <NA> 12010 13670 0 <NA>
## . ... ... ... ... ... ... ...
## 1 <NA> <NA> 5826 5891 0 <NA>
## 1 <NA> <NA> 7446 7514 0 <NA>
## 1 14149 14673 14149 14673 525 <NA>
## 1 <NA> <NA> 14674 14742 0 <NA>
## 1 <NA> <NA> 15956 16023 0 <NA>
## exon_end
## <integer>
## <NA>
## <NA>
## <NA>
## <NA>
## <NA>
## . ...
## <NA>
## <NA>
## <NA>
## <NA>
## <NA>
## -------
## seqinfo: 25 sequences (1 circular) from hg38 genome
The function queryTxObject in crisprDesign is a user-friendly
function to work with such objects, for instance once can return the CDS
coordinates for the KRAS transcripts using the following lines of code:
library(crisprDesign)
cds <- queryTxObject(txdb_human,
featureType="cds",
queryColumn="gene_symbol",
queryValue="KRAS")
head(cds)## GRanges object with 6 ranges and 14 metadata columns:
## seqnames ranges strand | tx_id gene_id
## <Rle> <IRanges> <Rle> | <character> <character>
## region_1 chr12 25245274-25245384 - | ENST00000256078 ENSG00000133703
## region_2 chr12 25227234-25227412 - | ENST00000256078 ENSG00000133703
## region_3 chr12 25225614-25225773 - | ENST00000256078 ENSG00000133703
## region_4 chr12 25215441-25215560 - | ENST00000256078 ENSG00000133703
## region_5 chr12 25245274-25245384 - | ENST00000311936 ENSG00000133703
## region_6 chr12 25227234-25227412 - | ENST00000311936 ENSG00000133703
## protein_id tx_type gene_symbol exon_id exon_rank
## <character> <character> <character> <character> <integer>
## region_1 ENSP00000256078 protein_coding KRAS ENSE00000936617 2
## region_2 ENSP00000256078 protein_coding KRAS ENSE00001719809 3
## region_3 ENSP00000256078 protein_coding KRAS ENSE00001644818 4
## region_4 ENSP00000256078 protein_coding KRAS ENSE00001189807 5
## region_5 ENSP00000308495 protein_coding KRAS ENSE00000936617 2
## region_6 ENSP00000308495 protein_coding KRAS ENSE00001719809 3
## cds_start cds_end tx_start tx_end cds_len exon_start
## <integer> <integer> <integer> <integer> <integer> <integer>
## region_1 <NA> <NA> 25205246 25250929 570 25245274
## region_2 <NA> <NA> 25205246 25250929 570 25227234
## region_3 <NA> <NA> 25205246 25250929 570 25225614
## region_4 <NA> <NA> 25205246 25250929 570 25215437
## region_5 <NA> <NA> 25205246 25250929 567 25245274
## region_6 <NA> <NA> 25205246 25250929 567 25227234
## exon_end
## <integer>
## region_1 25245395
## region_2 25227412
## region_3 25225773
## region_4 25215560
## region_5 25245395
## region_6 25227412
## -------
## seqinfo: 25 sequences (1 circular) from hg38 genome
The tss_human and tss_mouse objects are GRanges representing the
transcription starting sites (TSSs) coordinates for human and mouse,
respectively. The coordinates were extracted from the transcripts stored
in the Ensembl-based models txdb_human and txdb_mouse using the
function getTssObjectFromTxObject from crisprDesign. See the script
generateTssObjects.Rin the inst folder to see how to generate such
data.
Let’s take a look at tss_human:
data(tss_human, package="crisprDesignData")
head(tss_human)## GRanges object with 6 ranges and 9 metadata columns:
## seqnames ranges strand | score peak_start peak_end
## <Rle> <IRanges> <Rle> | <numeric> <integer> <integer>
## ENSG00000000003_P1 chrX 100636805 - | 4.35417 100636805 100636805
## ENSG00000000005_P1 chrX 100584935 + | 3.29137 100584935 100584935
## ENSG00000000419_P1 chr20 50958531 - | 5.74747 50958531 50958531
## ENSG00000000457_P1 chr1 169893895 - | 4.75432 169893895 169893895
## ENSG00000000460_P1 chr1 169795044 + | 4.92777 169795044 169795044
## ENSG00000000938_P1 chr1 27635184 - | 4.61214 27635184 27635184
## tx_id gene_id source promoter
## <character> <character> <character> <character>
## ENSG00000000003_P1 ENST00000373020 ENSG00000000003 fantom5 P1
## ENSG00000000005_P1 ENST00000373031 ENSG00000000005 fantom5 P1
## ENSG00000000419_P1 ENST00000371588 ENSG00000000419 fantom5 P1
## ENSG00000000457_P1 ENST00000367771 ENSG00000000457 fantom5 P1
## ENSG00000000460_P1 ENST00000359326 ENSG00000000460 fantom5 P1
## ENSG00000000938_P1 ENST00000374005 ENSG00000000938 fantom5 P1
## ID gene_symbol
## <character> <character>
## ENSG00000000003_P1 ENSG00000000003_P1 TSPAN6
## ENSG00000000005_P1 ENSG00000000005_P1 TNMD
## ENSG00000000419_P1 ENSG00000000419_P1 DPM1
## ENSG00000000457_P1 ENSG00000000457_P1 SCYL3
## ENSG00000000460_P1 ENSG00000000460_P1 C1orf112
## ENSG00000000938_P1 ENSG00000000938_P1 FGR
## -------
## seqinfo: 25 sequences from an unspecified genome; no seqlengths
The function queryTss in crisprDesign is a user-friendly function to
work with such objects, accepting an argument called tss_window to
specify a number of nucleotides upstream and downstream of the TSS. This
is particularly useful to return genomic regions to target for CRISPRa
and CRISPRi.
For instance, if we want to target the region 500 nucleotides upstream of any of the KRAS TSSs, one can use the following lines of code:
library(crisprDesign)
tss <- queryTss(tss_human,
queryColumn="gene_symbol",
queryValue="KRAS",
tss_window=c(-500,0))
head(tss)## GRanges object with 1 range and 9 metadata columns:
## seqnames ranges strand | score peak_start peak_end
## <Rle> <IRanges> <Rle> | <numeric> <integer> <integer>
## region_1 chr12 25250929-25251428 - | 5.20187 25250928 25250928
## tx_id gene_id source promoter
## <character> <character> <character> <character>
## region_1 ENST00000256078 ENSG00000133703 fantom5 P1
## ID gene_symbol
## <character> <character>
## region_1 ENSG00000133703_P1 KRAS
## -------
## seqinfo: 25 sequences from an unspecified genome; no seqlengths
The mrnasHuman and mrnasMouse objects are DNAStringSet storing the
nucleotide sequence of mRNAs derived from the txdb_human and
txdb_mouse gene models, respectively. It was obtained using the
function getMrnaSequences from crisprDesign. See the script
generateMrnaData.Rin the inst folder to see how to generate such
data. The names of the DNAStringSet are Ensembl transcript IDs:
data(mrnasHuman, package="crisprDesignData")
data(mrnasMouse, package="crisprDesignData")
head(mrnasHuman)## DNAStringSet object of length 6:
## width seq names
## [1] 1032 CTGCTGCTGCTGCGCCCCATCCC...TAATAAATTTGCTGTGGTTTGTA ENST00000000233
## [2] 2450 AGAGTGGGGCACAGCGAGGCGCT...GATTAAAAAACAAACAAAACATA ENST00000000412
## [3] 2274 GTCAGCTGGAGGAAGCGGAGTAG...ATATATAATACCGAGCTCAAAAA ENST00000000442
## [4] 3715 CCTACCCCAGCTCTCGCGCCGCG...CTAGTGAGGATGTTTTGTTAAAA ENST00000001008
## [5] 4556 ACAGCCAATCCCCCGAGCGGCCG...TAGAATAAACCGTGGGGACCCGC ENST00000001146
## [6] 2184 GTCTAAGCCCCAGCTCCTGGCGG...ACGAGTAATTTCATAGAAACGAA ENST00000002125
head(mrnasMouse)## DNAStringSet object of length 6:
## width seq names
## [1] 3262 CACACATCCGGTTCTTCCGGGAG...TTCTTCACTTCTTTGTCTCTGCA ENSMUST00000000001
## [2] 902 GTCAGTGCACAACTGCCAACTGG...TTAAATAAATTTATTTTACTTGC ENSMUST00000000003
## [3] 2574 GGTCCGTGTGCCACCTTTTCCCT...AATATACATATCACTCTAGAAAA ENSMUST00000000010
## [4] 2143 TGGAAACACATTCAAATAATGTG...AAAATGTTTGATGTTTTATCCCC ENSMUST00000000028
## [5] 3708 GGCACTGACCAGTTCGCAAACTG...AATAAAGCATTTAAAATACTATT ENSMUST00000000033
## [6] 1190 TCTCTTCAGCAGAAGACACCACT...AAGTTACTGGATTGCCTCAGTTA ENSMUST00000000049
Those objects are particularly useful for gRNA design for RNA-targeting nucleases such as RfxCas13d (CasRx).
The objects gr.repeats.hg38 and gr.repeats.mm10 objects are
GRanges representing the genomic coordinates of repeat elements in the
human and mouse genomes, as defined by the RepeatMasker tracks in the
UCSC genome browser.
Let’s look at the repeats elements in the human genome:
data(gr.repeats.hg38, package="crisprDesignData")
head(gr.repeats.hg38)## GRanges object with 6 ranges and 2 metadata columns:
## seqnames ranges strand | type score
## <Rle> <IRanges> <Rle> | <character> <numeric>
## [1] chr1 67108753-67109046 + | L1P5 1892
## [2] chr1 8388315-8388618 - | AluY 2582
## [3] chr1 25165803-25166380 + | L1MB5 4085
## [4] chr1 33554185-33554483 - | AluSc 2285
## [5] chr1 41942894-41943205 - | AluY 2451
## [6] chr1 50331336-50332274 + | HAL1 1587
## -------
## seqinfo: 25 sequences (1 circular) from hg38 genome
The data.frames canonicalHuman and canonicalMouse contains
information about Ensembl canonical transcripts for human and mouse
respectively. The Ensembl canonical transcript is the best
well-supported, biologically representative, highly expressed, and
highly conserved transcript for a given gene. MANE Select is used as the
canonical transcript for human protein coding genes where available.
data(canonicalHuman, package="crisprDesignData")
head(canonicalHuman)## tx_id gene_id
## 1 ENST00000272065 ENSG00000143727
## 2 ENST00000329066 ENSG00000115705
## 3 ENST00000252505 ENSG00000151360
## 4 ENST00000256509 ENSG00000134121
## 5 ENST00000349077 ENSG00000118004
## 6 ENST00000273130 ENSG00000144635
The DataFrame objects pfamTableHuman and pfamTableMouse contains
Pfam domains retrieved from biomaRt for human and mouse transcripts.
data(pfamTableHuman, package="crisprDesignData")
head(pfamTableHuman)## DataFrame with 6 rows and 4 columns
## ensembl_transcript_id pfam pfam_start pfam_end
## <character> <character> <integer> <integer>
## 1 ENST00000673477 PF12037 41 286
## 2 ENST00000673477 PF00004 348 474
## 3 ENST00000308647 PF12037 40 96
## 4 ENST00000308647 PF12037 99 180
## 5 ENST00000308647 PF00004 242 294
## 6 ENST00000511072 PF13912 231 251
The pfam_start and pfam_end columns contain the amino acid
coordinates of the domain start and end, respectively, and the pfam
column contains the Pfam domain ID.
The package is licensed under the MIT license.
sessionInfo()## R version 4.2.1 (2022-06-23)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] crisprDesign_0.99.176 crisprBase_1.1.8 GenomicRanges_1.49.1
## [4] GenomeInfoDb_1.33.7 IRanges_2.31.2 S4Vectors_0.35.3
## [7] BiocGenerics_0.43.4 crisprDesignData_0.99.23
##
## loaded via a namespace (and not attached):
## [1] bitops_1.0-7 matrixStats_0.62.0
## [3] bit64_4.0.5 filelock_1.0.2
## [5] progress_1.2.2 httr_1.4.4
## [7] tools_4.2.1 utf8_1.2.2
## [9] R6_2.5.1 DBI_1.1.3
## [11] tidyselect_1.1.2 prettyunits_1.1.1
## [13] bit_4.0.4 curl_4.3.2
## [15] compiler_4.2.1 crisprBowtie_1.1.1
## [17] cli_3.4.0 Biobase_2.57.1
## [19] basilisk.utils_1.9.3 crisprScoreData_1.1.3
## [21] xml2_1.3.3 DelayedArray_0.23.1
## [23] rtracklayer_1.57.0 randomForest_4.7-1.1
## [25] readr_2.1.2 rappdirs_0.3.3
## [27] stringr_1.4.1 digest_0.6.29
## [29] Rsamtools_2.13.4 rmarkdown_2.16
## [31] crisprScore_1.1.15 basilisk_1.9.6
## [33] XVector_0.37.1 pkgconfig_2.0.3
## [35] htmltools_0.5.3 MatrixGenerics_1.9.1
## [37] dbplyr_2.2.1 fastmap_1.1.0
## [39] BSgenome_1.65.2 rlang_1.0.5
## [41] rstudioapi_0.14 RSQLite_2.2.16
## [43] shiny_1.7.2 BiocIO_1.7.1
## [45] generics_0.1.3 jsonlite_1.8.0
## [47] BiocParallel_1.31.12 dplyr_1.0.10
## [49] VariantAnnotation_1.43.3 RCurl_1.98-1.8
## [51] magrittr_2.0.3 GenomeInfoDbData_1.2.8
## [53] Matrix_1.4-1 Rcpp_1.0.9
## [55] fansi_1.0.3 reticulate_1.26
## [57] Rbowtie_1.37.0 lifecycle_1.0.1
## [59] stringi_1.7.8 yaml_2.3.5
## [61] SummarizedExperiment_1.27.2 zlibbioc_1.43.0
## [63] AnnotationHub_3.5.1 BiocFileCache_2.5.0
## [65] grid_4.2.1 blob_1.2.3
## [67] promises_1.2.0.1 parallel_4.2.1
## [69] ExperimentHub_2.5.0 crayon_1.5.1
## [71] dir.expiry_1.5.1 lattice_0.20-45
## [73] Biostrings_2.65.3 GenomicFeatures_1.49.6
## [75] hms_1.1.2 KEGGREST_1.37.3
## [77] knitr_1.40 pillar_1.8.1
## [79] rjson_0.2.21 codetools_0.2-18
## [81] biomaRt_2.53.2 BiocVersion_3.16.0
## [83] XML_3.99-0.10 glue_1.6.2
## [85] evaluate_0.16 BiocManager_1.30.18
## [87] httpuv_1.6.5 png_0.1-7
## [89] vctrs_0.4.1 tzdb_0.3.0
## [91] purrr_0.3.4 assertthat_0.2.1
## [93] cachem_1.0.6 xfun_0.32
## [95] mime_0.12 xtable_1.8-4
## [97] restfulr_0.0.15 later_1.3.0
## [99] tibble_3.1.8 GenomicAlignments_1.33.1
## [101] AnnotationDbi_1.59.1 memoise_2.0.1
## [103] interactiveDisplayBase_1.35.0 ellipsis_0.3.2