Design sgRNAs  

This tool ranks and picks candidate sgRNA sequences for the targets provided, while attempting to maximize on-target activity and minimizing off-target activity using Rule Set 2 on-target scoring and the CFD (Cutting Frequency Determination) score to evaluate off-target sites.

For detailed instructions on how to use this tool, please see our sgRNA Designer Help Page. Please also visit the related sgRNA Scoring Help Page for details on Rule Set 2 (as described in Doench, Fusi et al., Nature Biotechnology 2016) and CFD scoring methods as well as Addgene for further discussion on sgRNA design. Mouse and human libraries designed using Rule Set 2 will be available shortly via Addgene.

NOTE: the scope of this tool is currently limited to the S. pyogenes (NGG) PAM--i.e. only NGG on-target sites are considered, and off-target CFD scores are computed relative to a preferred NGG PAM.

NOTE: On 6/11/2016, a bug was discovered in our Rule Set 2 on-target scoring algorithm that affected a subset of guide scores, which has since been fixed. For reference, we compared Rule Set 2 scores before and after the bug fix for 1000 randomly chosen sgRNAs. For 986 (98.6%) there was no difference in score to the fourth decimal place. For the remaining 14 sgRNAs, the average difference was 3.1%, with a maximal difference of 5.3%.

Looking for the old version of this tool? Go here.
Looking for a downloadable tool to compute Rule Set 2 and CFD scores for existing sgRNA designs? Go here.

This form accepts up to 10 Human or Mouse RefSeq transcript IDs (e.g., NM_014911, NM_014911.3, etc.) or a single nucleotide sequence of at least 30 bases.
File inputs must be smaller than 10kb in size, and any sequences submitted via file must be in FASTA format.
This field is required only when targeting DNA sequences (i.e. if you pasted or uploaded raw DNA sequences rather than RefSeq transcript IDs).
This tool not only ranks all candidate sgRNA sequences for each target, but it will also select (or "pick") the top N such candidates according the raw ranking, as well as other criteria such as cut position and mutual spacing. If you don't care about this, you can safely ignore the "Pick Order" and related columns in the output file, and just use the raw ranking columns as desired.
If checked, then all possible candidates for each target will be returned (the picked ones will still be marked). If unchecked, then the result file will be limited to the sgRNA sequences actually picked to fulfill your quota.