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GitHub Repository (legacy)
The links marked legacy point to the original published source code. For the model as this web server runs it, use the Download Model link above.
DeepSmallCas9 is a deep learning-based web tool that designs guide RNAs and predicts their efficiencies for 17 small Cas9 orthologs and variants.
It supports prediction for:
sRGN3.1
SlugCas9, SlugCas9-HF
SaCas9, SaCas9-KKH, SaCas9-HF, SaCas9-KKH-HF, eSaCas9, efSaCas9
SauriCas9, SauriCas9-KKH
Sa-SlugCas9
St1Cas9
Nm1Cas9, Nm2Cas9
CjCas9, enCjCas9
The list of supported gene inputs are available in Human Genes Set and Mouse Genes Set.
Homology-directed repair (HDR) donor templates. When an input format describes an intended edit — an unedited/edited sequence pair, ClinVar ID or COSMIC ID — the results also carry what each guide needs for HDR: the cut site, the cut-to-edit distance, the donor template in the chosen type and orientation(s) (default: a single-stranded oligo on the sense strand, 100 nt homology arms each side), the realised arm lengths, an optional PAM-blocking mutation, and the candidate's rank among the target's guides. There is no HDR mode switch: the input format decides.