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4 changes: 2 additions & 2 deletions DESCRIPTION
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Package: crisprScore
Version: 1.1.16
Date: 2022-10-22
Version: 1.1.17
Date: 2022-10-17
Title: On-Target and Off-Target Scoring Algorithms for CRISPR gRNAs
Authors@R: c(
person("Jean-Philippe", "Fortin", email = "fortin946@gmail.com", role = c("aut", "cre", "cph")),
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10 changes: 6 additions & 4 deletions README.Rmd
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Expand Up @@ -10,24 +10,26 @@ bibliography: vignettes/references.bib
options("knitr.graphics.auto_pdf"=TRUE)
```

Authors: Jean-Philippe Fortin, Aaron Lun, Luke Hoberecht
Authors: Jean-Philippe Fortin, Aaron Lun, Luke Hoberecht, Pirunthan Perampalan

Date: July 1, 2022

# Overview

crisprScore provides R wrappers of several on-target and off-target scoring
The `crisprScore` package provides R wrappers of several on-target and off-target scoring
methods for CRISPR guide RNAs (gRNAs). The following nucleases are supported:
SpCas9, AsCas12a, enAsCas12a, and RfxCas13d (CasRx). The available on-target
cutting efficiency scoring methods are RuleSet1, RuleSet3, Azimuth, DeepHF,
DeepSpCas9, DeepCpf1, enPAM+GB, CRISPRscan and CRISPRater. Both the CFD and MIT
DeepSpCas9, DeepCpf1, enPAM+GB, CRISPRscan and CRISPRater. Both the CFD and MIT
scoring methods are available for off-target specificity prediction. The
package also provides a Lindel-derived score to predict the probability
of a gRNA to produce indels inducing a frameshift for the Cas9 nuclease.
Note that DeepHF, DeepCpf1 and enPAM+GB are not available on Windows machines.

Our work is described in a recent bioRxiv preprint:
["A comprehensive Bioconductor ecosystem for the design of CRISPR guide RNAs across nucleases and technologies"](https://www.biorxiv.org/content/10.1101/2022.04.21.488824v2)
["The crisprVerse: A comprehensive Bioconductor ecosystem for the design of CRISPR guide RNAs across nucleases and technologies"](https://www.biorxiv.org/content/10.1101/2022.04.21.488824v3)

Our main gRNA design package [crisprDesign](https://github.com/crisprVerse/crisprDesign) utilizes the `crisprScore` package to add on- and off-target scores to user-designed gRNAs; check out our [Cas9 gRNA tutorial page](https://github.com/crisprVerse/Tutorials/tree/master/Design_CRISPRko_Cas9) to learn how to use `crisprScore` via `crisprDesign`.


# Installation and getting started
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70 changes: 39 additions & 31 deletions README.md
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Expand Up @@ -43,27 +43,35 @@ crisprScore: on-target and off-target scoring for CRISPR gRNAs
- <a href="#reproducibility" id="toc-reproducibility">Reproducibility</a>
- <a href="#references" id="toc-references">References</a>

Authors: Jean-Philippe Fortin, Aaron Lun, Luke Hoberecht
Authors: Jean-Philippe Fortin, Aaron Lun, Luke Hoberecht, Pirunthan
Perampalan

Date: July 1, 2022

# Overview

crisprScore provides R wrappers of several on-target and off-target
scoring methods for CRISPR guide RNAs (gRNAs). The following nucleases
are supported: SpCas9, AsCas12a, enAsCas12a, and RfxCas13d (CasRx). The
available on-target cutting efficiency scoring methods are RuleSet1,
RuleSet3, Azimuth, DeepHF, DeepSpCas9, DeepCpf1, enPAM+GB, CRISPRscan
and CRISPRater. Both the CFD and MIT scoring methods are available for
off-target specificity prediction. The package also provides a
Lindel-derived score to predict the probability of a gRNA to produce
indels inducing a frameshift for the Cas9 nuclease. Note that DeepHF,
DeepCpf1 and enPAM+GB are not available on Windows machines.

Our work is described in a recent bioRxiv preprint: [“A comprehensive
Bioconductor ecosystem for the design of CRISPR guide RNAs across
nucleases and
technologies”](https://www.biorxiv.org/content/10.1101/2022.04.21.488824v2)
The `crisprScore` package provides R wrappers of several on-target and
off-target scoring methods for CRISPR guide RNAs (gRNAs). The following
nucleases are supported: SpCas9, AsCas12a, enAsCas12a, and RfxCas13d
(CasRx). The available on-target cutting efficiency scoring methods are
RuleSet1, RuleSet3, Azimuth, DeepHF, DeepSpCas9, DeepCpf1, enPAM+GB,
CRISPRscan and CRISPRater. Both the CFD and MIT scoring methods are
available for off-target specificity prediction. The package also
provides a Lindel-derived score to predict the probability of a gRNA to
produce indels inducing a frameshift for the Cas9 nuclease. Note that
DeepHF, DeepCpf1 and enPAM+GB are not available on Windows machines.

Our work is described in a recent bioRxiv preprint: [“The crisprVerse: A
comprehensive Bioconductor ecosystem for the design of CRISPR guide RNAs
across nucleases and
technologies”](https://www.biorxiv.org/content/10.1101/2022.04.21.488824v3)

Our main gRNA design package
[crisprDesign](https://github.com/crisprVerse/crisprDesign) utilizes the
`crisprScore` package to add on- and off-target scores to user-designed
gRNAs; check out our [Cas9 gRNA tutorial
page](https://github.com/crisprVerse/Tutorials/tree/master/Design_CRISPRko_Cas9)
to learn how to use `crisprScore` via `crisprDesign`.

# Installation and getting started

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## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] crisprScore_1.1.14 crisprScoreData_1.1.3 ExperimentHub_2.5.0
## [4] AnnotationHub_3.5.0 BiocFileCache_2.5.0 dbplyr_2.2.1
## [7] BiocGenerics_0.43.1
## [1] crisprScore_1.1.15 crisprScoreData_1.1.3 ExperimentHub_2.5.0
## [4] AnnotationHub_3.5.1 BiocFileCache_2.5.0 dbplyr_2.2.1
## [7] BiocGenerics_0.43.4
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.9 lattice_0.20-45
## [3] dir.expiry_1.5.0 png_0.1-7
## [5] Biostrings_2.65.2 assertthat_0.2.1
## [3] dir.expiry_1.5.1 png_0.1-7
## [5] Biostrings_2.65.3 assertthat_0.2.1
## [7] digest_0.6.29 utf8_1.2.2
## [9] mime_0.12 R6_2.5.1
## [11] GenomeInfoDb_1.33.5 stats4_4.2.1
## [11] GenomeInfoDb_1.33.7 stats4_4.2.1
## [13] RSQLite_2.2.16 evaluate_0.16
## [15] highr_0.9 httr_1.4.4
## [17] pillar_1.8.1 basilisk_1.9.3
## [19] zlibbioc_1.43.0 rlang_1.0.4
## [17] pillar_1.8.1 basilisk_1.9.6
## [19] zlibbioc_1.43.0 rlang_1.0.5
## [21] curl_4.3.2 rstudioapi_0.14
## [23] blob_1.2.3 S4Vectors_0.35.1
## [25] Matrix_1.4-1 reticulate_1.25
## [27] rmarkdown_2.15.2 stringr_1.4.1
## [23] blob_1.2.3 S4Vectors_0.35.3
## [25] Matrix_1.4-1 reticulate_1.26
## [27] rmarkdown_2.16 stringr_1.4.1
## [29] RCurl_1.98-1.8 bit_4.0.4
## [31] shiny_1.7.2 compiler_4.2.1
## [33] httpuv_1.6.5 xfun_0.32
Expand All @@ -670,14 +678,14 @@ sessionInfo()
## [39] tibble_3.1.8 GenomeInfoDbData_1.2.8
## [41] interactiveDisplayBase_1.35.0 IRanges_2.31.2
## [43] randomForest_4.7-1.1 fansi_1.0.3
## [45] crayon_1.5.1 dplyr_1.0.9
## [47] later_1.3.0 basilisk.utils_1.9.1
## [45] crayon_1.5.1 dplyr_1.0.10
## [47] later_1.3.0 basilisk.utils_1.9.3
## [49] bitops_1.0-7 rappdirs_0.3.3
## [51] grid_4.2.1 jsonlite_1.8.0
## [53] xtable_1.8-4 lifecycle_1.0.1
## [55] DBI_1.1.3 magrittr_2.0.3
## [57] cli_3.3.0 stringi_1.7.8
## [59] cachem_1.0.6 XVector_0.37.0
## [57] cli_3.4.0 stringi_1.7.8
## [59] cachem_1.0.6 XVector_0.37.1
## [61] promises_1.2.0.1 ellipsis_0.3.2
## [63] filelock_1.0.2 generics_0.1.3
## [65] vctrs_0.4.1 tools_4.2.1
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7 changes: 4 additions & 3 deletions vignettes/crisprScore.Rmd
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Expand Up @@ -29,19 +29,20 @@ options("knitr.graphics.auto_pdf"=TRUE)

# Overview

crisprScore provides R wrappers of several on-target and off-target scoring
The `crisprScore` package provides R wrappers of several on-target and off-target scoring
methods for CRISPR guide RNAs (gRNAs). The following nucleases are supported:
SpCas9, AsCas12a, enAsCas12a, and RfxCas13d (CasRx). The available on-target
cutting efficiency scoring methods are RuleSet1, RuleSet3, Azimuth, DeepHF,
DeepSpCas9, DeepCpf1, enPAM+GB, CRISPRscan and CRISPRater. Both the CFD and MIT
DeepSpCas9, DeepCpf1, enPAM+GB, CRISPRscan and CRISPRater. Both the CFD and MIT
scoring methods are available for off-target specificity prediction. The
package also provides a Lindel-derived score to predict the probability
of a gRNA to produce indels inducing a frameshift for the Cas9 nuclease.
Note that DeepHF, DeepCpf1 and enPAM+GB are not available on Windows machines.

Our work is described in a recent bioRxiv preprint:
["A comprehensive Bioconductor ecosystem for the design of CRISPR guide RNAs across nucleases and technologies"](https://www.biorxiv.org/content/10.1101/2022.04.21.488824v2)
["The crisprVerse: A comprehensive Bioconductor ecosystem for the design of CRISPR guide RNAs across nucleases and technologies"](https://www.biorxiv.org/content/10.1101/2022.04.21.488824v3)

Our main gRNA design package [crisprDesign](https://github.com/crisprVerse/crisprDesign) utilizes the `crisprScore` package to add on- and off-target scores to user-designed gRNAs; check out our [Cas9 gRNA tutorial page](https://github.com/crisprVerse/Tutorials/tree/master/Design_CRISPRko_Cas9) to learn how to use `crisprScore` via `crisprDesign`.

# Installation and getting started

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