GPP sgRNA Designer

Soon to be relaunched as CRISPick. Please check this space for updates.

Input Transcript IDs, Gene IDs/Symbols, or raw DNA sequence:
Upload a list of Transcript IDs, Gene IDs/Symbols, or a FASTA file of DNA sequences:
Enter up to 200 Transcript IDs (e.g., NM_014911.3, ENST00000456328, etc.), Gene IDs or Symbols (e.g., 988, CDC5L, ENSG00000223972, etc.), or a single DNA sequence.

File inputs must be smaller than 20kb in size, and any sequences submitted via file must be in FASTA format.

Please refer to our sgRNA Designer Help Page for details on how a transcript is chosen for a gene input.

About this tool

This tool ranks and picks candidate CRISPRko sgRNA sequences for the targets provided, while attempting to maximize on-target activity and minimizing off-target activity. For more information about the inputs and outputs of this tool, see How to use the GPP sgRNA Designer (CRISPRko) or How to use the GPP sgRNA Designer (CRISPRa/i).

On-target scoring is performed using Azimuth 2.0 [1][2] for SpyoCas9 and SaurCas9 systems, Seq-DeepCpf1 [3] for AsCas12a and enPAM+GB [4] for enAsCas12a. Off-target sites are evaluated using the CFD (Cutting Frequency Determination) score. Please see How the sgRNA Designer Works for more details on these annotation strategies. For general discussion on sgRNA design, see Addgene.

For notes about revisions, updates, and bug fixes please see the GPP sgRNA Designer Changelog.


  1. Doench, J. G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E. W., Donovan, K. F., … Root, D. E. (2016). Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nature biotechnology, 34(2), 184-191. doi:10.1038/nbt.3437 [Nat Biotechnol]
  2. Sanson, K. R., Hanna, R. E., Hegde, M., Donovan, K. F., Strand, C., Sullender, M. E., … Doench, J. G. (2018). Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities. Nature communications, 9(1), 5416. doi:10.1038/s41467-018-07901-8 [Nat Commun]
  3. Kim, H., Min, S., Song, M., Jung, S., Choi, J. W., … Kim, H. (2018). Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity. Nat Biotechnol 36, 239–241. [Nat Biotechnol]
  4. Sanson, K. R., DeWeirdt, P. C., Sangree, A. K., Hanna, R. E., Hegde, M., Teng, T., … Doench, J. G. (2020). Optimization of AsCas12a for combinatorial genetic screens in human cells. bioRxiv Preprint. [bioRxiv Preprint]