crisprverse / crisprviz

Visualization of CRISPR guide RNAs (gRNAs)

crisprVerse: ecosystem of R packages for CRISPR gRNA design

• Installation and getting started
• Components
• Reproducibility

Authors: Jean-Philippe Fortin, Luke Hoberecht

Date: July 25, 2022

Installation and getting started

The crisprVerse is a collection of packages for CRISPR guide RNA (gRNA) design that can easily be installed with the crisprVerse package. This provides a convenient way of downloading and installing all crisprVerse packages with a single R command.

The package can be installed from the Bioconductor devel branch using the following commands in an R session:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install(version="devel")
BiocManager::install("crisprVerse")

The core crisprVerse includes the packages that are commonly used for gRNA design, and are attached when you attach the crisprVerse package:

library(crisprVerse)

## Warning: multiple methods tables found for 'aperm'

## Warning: replacing previous import 'BiocGenerics::aperm' by
## 'DelayedArray::aperm' when loading 'SummarizedExperiment'

You can check that all crisprVerse packages are up-to-date with crisprVerse_update():

crisprVerse_update()

## The following packages are out of date:
## 
## • crisprDesign (0.99.176 -> 0.99.177)
## • crisprScore  (1.1.15 -> 1.1.16)
## 
## Start a clean R session then run:
## BiocManager::install(c("crisprDesign", "crisprScore"))

The complete documentation for the package can be found here.

Components

The following packages are installed and loaded with the crisprVerse package:

• crisprBase to specify and manipulate CRISPR nucleases.
• crisprBowtie to perform gRNA spacer sequence alignment with Bowtie.
• crisprScore to annotate gRNAs with on-target and off-target scores.
• crisprDesign to design and manipulate gRNAs with GuideSet objects.
• crisprViz to visualize gRNAs.

Reproducibility

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] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] crisprViz_0.99.22     crisprDesign_0.99.176 crisprScore_1.1.15   
##  [4] crisprScoreData_1.1.3 ExperimentHub_2.5.0   AnnotationHub_3.5.1  
##  [7] BiocFileCache_2.5.0   dbplyr_2.2.1          BiocGenerics_0.43.4  
## [10] crisprBowtie_1.1.1    crisprBase_1.1.8      crisprVerse_0.99.9   
## [13] BiocStyle_2.25.0     
## 
## loaded via a namespace (and not attached):
##   [1] backports_1.4.1               Hmisc_4.7-1                  
##   [3] lazyeval_0.2.2                splines_4.2.1                
##   [5] BiocParallel_1.31.12          GenomeInfoDb_1.33.7          
##   [7] ggplot2_3.3.6                 digest_0.6.29                
##   [9] ensembldb_2.21.4              htmltools_0.5.3              
##  [11] fansi_1.0.3                   checkmate_2.1.0              
##  [13] magrittr_2.0.3                memoise_2.0.1                
##  [15] BSgenome_1.65.2               cluster_2.1.4                
##  [17] tzdb_0.3.0                    Biostrings_2.65.3            
##  [19] readr_2.1.2                   matrixStats_0.62.0           
##  [21] prettyunits_1.1.1             jpeg_0.1-9                   
##  [23] colorspace_2.0-3              blob_1.2.3                   
##  [25] rappdirs_0.3.3                xfun_0.32                    
##  [27] dplyr_1.0.10                  crayon_1.5.1                 
##  [29] RCurl_1.98-1.8                jsonlite_1.8.0               
##  [31] survival_3.4-0                VariantAnnotation_1.43.3     
##  [33] glue_1.6.2                    gtable_0.3.1                 
##  [35] zlibbioc_1.43.0               XVector_0.37.1               
##  [37] DelayedArray_0.23.1           scales_1.2.1                 
##  [39] DBI_1.1.3                     Rcpp_1.0.9                   
##  [41] htmlTable_2.4.1               xtable_1.8-4                 
##  [43] progress_1.2.2                reticulate_1.26              
##  [45] foreign_0.8-82                bit_4.0.4                    
##  [47] Formula_1.2-4                 stats4_4.2.1                 
##  [49] htmlwidgets_1.5.4             httr_1.4.4                   
##  [51] dir.expiry_1.5.1              RColorBrewer_1.1-3           
##  [53] ellipsis_0.3.2                pkgconfig_2.0.3              
##  [55] XML_3.99-0.10                 nnet_7.3-17                  
##  [57] Gviz_1.41.1                   deldir_1.0-6                 
##  [59] utf8_1.2.2                    tidyselect_1.1.2             
##  [61] rlang_1.0.5                   later_1.3.0                  
##  [63] AnnotationDbi_1.59.1          munsell_0.5.0                
##  [65] BiocVersion_3.16.0            tools_4.2.1                  
##  [67] cachem_1.0.6                  cli_3.4.0                    
##  [69] generics_0.1.3                RSQLite_2.2.16               
##  [71] evaluate_0.16                 stringr_1.4.1                
##  [73] fastmap_1.1.0                 yaml_2.3.5                   
##  [75] knitr_1.40                    bit64_4.0.5                  
##  [77] purrr_0.3.4                   randomForest_4.7-1.1         
##  [79] AnnotationFilter_1.21.0       KEGGREST_1.37.3              
##  [81] Rbowtie_1.37.0                mime_0.12                    
##  [83] xml2_1.3.3                    biomaRt_2.53.2               
##  [85] compiler_4.2.1                rstudioapi_0.14              
##  [87] filelock_1.0.2                curl_4.3.2                   
##  [89] png_0.1-7                     interactiveDisplayBase_1.35.0
##  [91] tibble_3.1.8                  stringi_1.7.8                
##  [93] basilisk.utils_1.9.3          GenomicFeatures_1.49.6       
##  [95] lattice_0.20-45               ProtGenerics_1.29.0          
##  [97] Matrix_1.4-1                  vctrs_0.4.1                  
##  [99] pillar_1.8.1                  lifecycle_1.0.1              
## [101] BiocManager_1.30.18           data.table_1.14.2            
## [103] bitops_1.0-7                  httpuv_1.6.5                 
## [105] rtracklayer_1.57.0            GenomicRanges_1.49.1         
## [107] R6_2.5.1                      BiocIO_1.7.1                 
## [109] latticeExtra_0.6-30           promises_1.2.0.1             
## [111] gridExtra_2.3                 IRanges_2.31.2               
## [113] codetools_0.2-18              dichromat_2.0-0.1            
## [115] assertthat_0.2.1              SummarizedExperiment_1.27.2  
## [117] rjson_0.2.21                  GenomicAlignments_1.33.1     
## [119] Rsamtools_2.13.4              S4Vectors_0.35.3             
## [121] GenomeInfoDbData_1.2.8        parallel_4.2.1               
## [123] hms_1.1.2                     rpart_4.1.16                 
## [125] grid_4.2.1                    basilisk_1.9.6               
## [127] rmarkdown_2.16                MatrixGenerics_1.9.1         
## [129] biovizBase_1.45.0             Biobase_2.57.1               
## [131] shiny_1.7.2                   base64enc_0.1-3              
## [133] interp_1.1-3                  restfulr_0.0.15

crisprviz's Issues

crisprViz: Error in TxDb2GRangesList (.getBiomartData(txdb, organism) : Organism "NA" not recognized in biomaRt)

Really appreciate the crisprVerse team for this robust and versatile tool to visualize and annotate sgRNAs. I tried the crisprViz tool by using the example datasets provided (gpr21GuideSet and gpr21GeneModel), and it works perfectly fine, the same as in the tutorial

Now I am interested in visualizing my sgRNAs targeting a particular gene of interest. First to build a gene model, the subset of txdb_human (GRangesList) was retrieved from crisprDesignData (as mentioned in the documentation on how to build the gpr21GeneModel). This is the step-by-step of what I have tried:

1. Import the txdb_human (GRangesList) from crisprDesignData
2. Unlist the GRangesList object
3. Taking a subset of txdb_human by only selecting a gene and its canonical transcript (using subset function)
4. Create a 'type' column in the metadata to suit the required format input in makeTxDbFromGRanges
5. TxDb object successfully created by using makeTxDbFromGRanges function
6. Convert the TxDb object from step number 5 into GRangesList (the required format for plotGuideSet in crisprViz) by using TxDb2GRangesList

My plan is to directly run the plotGuideSet function after the GRangesList object is successfully created (already have the sgRNA GuideSet object). However, in the step 6, an error occurred :

> granges_list_gene_model <- TxDb2GRangesList(granges_gene_model_txdb, 
+                                             standardChromOnly = TRUE,
+                                             genome = 'hg38',
+                                             seqlevelsStyle = 'UCSC')
Error in .getBiomartData(txdb, organism) : 
Organism "NA" not recognized in biomaRt. You can use",
"organism=NULL as a solution.

I checked the genomeInfo inside the GRanges object of my gene model and compared it with the gpr21GeneModel. Both indicate the same Organism: Homo sapiens. Furthermore, I noticed the TxDb2GRangesList doesn't have a parameter to state what kind of organism the user can specify.

Looking at the source code, it turns out this function is linked with another function getTxDb which allows the user to specify the organism (default: Homo sapiens). Since specifying the organism is not a parameter in the TxDb2GRangesList function, this means the user doesn't have direct control over it. Despite it was stated that the user can use 'organism = NULL' as a solution.

Could any of the team assist in this error? in particular, the steps that I have taken so far or any other way around to resolve this issue, looking forward to hearing more soon.