A resource hub for enhancing CRISPR design
CRISPR gRNA activity datasets
List of compiled CRISPR activity datasets
Decision-tree based selection of CRISPR design tools
Level 1 Prediction of activity
| No | Cas-Designer |
| Yes | go to level 2 |
Level 2: Species specific
A Non-exhaustive list of CRISPR design tools
| Name | Supported Organism | Cas nuclease | Features | Ref | |
| CRISPOR | > 100 species | > 30 Cas9 orthologues and Cas variants | Designing, evaluating, and cloning guide sequences for the CRISPR/Cas9 system; providing primers for vector construction; showing mismatch number of off-targets and linking them into genome browser | [1] | |
| CHOPCHOP | > 100 species | Cas9, Cas9 nickase, Cas12, Cas13 | Providing multi-predictive results from different tools; appliable for multi-CRISPR application; visualizing genomic location of targets and genes; and providing primers | [2,3] | |
| CRISPRon | Human and other 7 species | SpCas9 | Designing of gRNAs for CRISPR/Cas9-mediated genome editing experiments based on deep-learning and energy parameters | [4] | |
| CRISPR RGEN Tools | > 100 species | > 20 Cas9 orthologs and Cas variants | Predicting latent off-targets via Cas-OFFinder, and out-of-frame scores via Microhomology Predictor; downloadable | [5,6] | |
| E-CRISP | > 50 species | SpCas9 | Feasibly creating genome-scale libraries; downloadable | [7] | |
| GUIDES | Human and mouse | SpCas9 | Feasibly designing CRISPR knockout libraries; downloadable; and step-by-step strategy | [8] | |
| CCTop | > 100 species | > 10 Cas9 orthologs and Cas variants | Detecting single and multiple queries; showing mismatch number; predicting off-target impacts; and predicting sgRNA efficiency using CRISPRater with custom in vitro transcription selection | [9] | |
| CRISPRz | Zebrafish, human, and mouse | SpCas9 | Providing specific for a wide variety of cell lines and organisms including Zebrafish; and providing validated sgRNA database | [10] | |
| CRISPR-P | 49 plant species | SpCas9 and its variants | Supporting wide range of plant species; providing on-target and off-target scoring; and gRNA sequence analysis | [11] | |
| EuPaGDT | Eukaryotic pathogens | > 10 Cas9 orthologs and Cas variants | Providing wide compatibility for eukaryotic pathogen genomes | [12] | |
| flyCRISPR | Drosophila and other organism | SpCas9 | Finding CRISPR target sites and evaluate each identified CRISPR target, specificity for drosophila | [13] | |
| CRISPRInc | 10 species | SpCas9 | Providing downloadable validated sgRNAs for lncRNAs | [14] | |
| SNP-CRISPR | 9 plant and animal species | SpCas9 with NGG and NAG PAM | Designing sgRNAs for targeting SNPs or Indel variants | [15] | |
| DeepHF | N/A | SpCas9, eSpCas9(1.1) and SpCas9-HF1 | gRNA efficiency prediction for specific Cas nucleases | [16] | |
| DeepSpCas9variants | N/A | Nine SpCas9 variants covering multi-PAMs | predicting the activities of nine SpCas9 variants | [17] | |
| DeepSmallCas9 | Human and mouse | > 10 small SpCas9 orthologs and variants | predicting the activities of seventeen small Cas9s | [18] | |
References
[1] M. Haeussler, K. Schonig, H. Eckert, A. Eschstruth, J. Mianne, J.B. Renaud, S. Schneider-Maunoury, A. Shkumatava, L. Teboul, J. Kent, J.S. Joly, J.P. Concordet, Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR, Genome Biol 17 (2016) 148. 10.1186/s13059-016-1012-2.
[2] K. Labun, T.G. Montague, J.A. Gagnon, S.B. Thyme, E. Valen, CHOPCHOP v2: a web tool for the next generation of CRISPR genome engineering, Nucleic Acids Res 44 (2016) W272-276. 10.1093/nar/gkw398.
[3] K. Labun, T.G. Montague, M. Krause, Y.N. Torres Cleuren, H. Tjeldnes, E. Valen, CHOPCHOP v3: expanding the CRISPR web toolbox beyond genome editing, Nucleic Acids Res 47 (2019) W171-W174. 10.1093/nar/gkz365.
[4] X. Xiang, G.I. Corsi, C. Anthon, K. Qu, X. Pan, X. Liang, P. Han, Z. Dong, L. Liu, J. Zhong, T. Ma, J. Wang, X. Zhang, H. Jiang, F. Xu, X. Liu, X. Xu, J. Wang, H. Yang, L. Bolund, G.M. Church, L. Lin, J. Gorodkin, Y. Luo, Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning, Nat Commun 12 (2021) 3238. 10.1038/s41467-021-23576-0.
[5] S. Bae, J. Kweon, H.S. Kim, J.S. Kim, Microhomology-based choice of Cas9 nuclease target sites, Nat Methods 11 (2014) 705-706. 10.1038/nmeth.3015.
[6] J. Park, S. Bae, J.S. Kim, Cas-Designer: a web-based tool for choice of CRISPR-Cas9 target sites, Bioinformatics 31 (2015) 4014-4016. 10.1093/bioinformatics/btv537.
[7] F. Heigwer, G. Kerr, M. Boutros, E-CRISP: fast CRISPR target site identification, Nat Methods 11 (2014) 122-123. 10.1038/nmeth.2812.
[8] J.A. Meier, F. Zhang, N.E. Sanjana, GUIDES: sgRNA design for loss-of-function screens, Nat Methods 14 (2017) 831-832. 10.1038/nmeth.4423.
[9] M. Stemmer, T. Thumberger, M. Del Sol Keyer, J. Wittbrodt, J.L. Mateo, CCTop: An Intuitive, Flexible and Reliable CRISPR/Cas9 Target Prediction Tool, PLoS One 10 (2015) e0124633. 10.1371/journal.pone.0124633.
[10] G.K. Varshney, S. Zhang, W. Pei, A. Adomako-Ankomah, J. Fohtung, K. Schaffer, B. Carrington, A. Maskeri, C. Slevin, T. Wolfsberg, J. Ledin, R. Sood, S.M. Burgess, CRISPRz: a database of zebrafish validated sgRNAs, Nucleic Acids Res 44 (2016) D822-826. 10.1093/nar/gkv998.
[11] H. Liu, Y. Ding, Y. Zhou, W. Jin, K. Xie, L.L. Chen, CRISPR-P 2.0: An Improved CRISPR-Cas9 Tool for Genome Editing in Plants, Mol Plant 10 (2017) 530-532. 10.1016/j.molp.2017.01.003.
[12] D. Peng, R. Tarleton, EuPaGDT: a web tool tailored to design CRISPR guide RNAs for eukaryotic pathogens, Microb Genom 1 (2015) e000033. 10.1099/mgen.0.000033.
[13] S.J. Gratz, F.P. Ukken, C.D. Rubinstein, G. Thiede, L.K. Donohue, A.M. Cummings, K.M. O'Connor-Giles, Highly specific and efficient CRISPR/Cas9-catalyzed homology-directed repair in Drosophila, Genetics 196 (2014) 961-971. 10.1534/genetics.113.160713.
[14] W. Chen, G. Zhang, J. Li, X. Zhang, S. Huang, S. Xiang, X. Hu, C. Liu, CRISPRlnc: a manually curated database of validated sgRNAs for lncRNAs, Nucleic Acids Res 47 (2019) D63-D68. 10.1093/nar/gky904.
[15] C.L. Chen, J. Rodiger, V. Chung, R. Viswanatha, S.E. Mohr, Y. Hu, N. Perrimon, SNP-CRISPR: A Web Tool for SNP-Specific Genome Editing, G3 (Bethesda) 10 (2020) 489-494. 10.1534/g3.119.400904.
[16] D. Wang, C. Zhang, B. Wang, B. Li, Q. Wang, D. Liu, H. Wang, Y. Zhou, L. Shi, F. Lan, Y. Wang, Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning, Nat Commun 10 (2019) 4284. 10.1038/s41467-019-12281-8.
[17] N. Kim, H.K. Kim, S. Lee, J.H. Seo, J.W. Choi, J. Park, S. Min, S. Yoon, S.R. Cho, H.H. Kim, Prediction of the sequence-specific cleavage activity of Cas9 variants, Nat Biotechnol 38 (2020) 1328-1336. 10.1038/s41587-020-0537-9.
[18] S.Y. Seo, S. Min, S. Lee, J.H. Seo, J. Park, H.K. Kim, M. Song, D. Baek, S.R. Cho, H.H. Kim, Massively parallel evaluation and computational prediction of the activities and specificities of 17 small Cas9s, Nat Methods 20 (2023) 999-1009. 10.1038/s41592-023-01875-2.