Abstract
We evaluated SpCas9 activities at 12,832 target sequences using a high-throughput approach based on a human cell library containing single-guide RNA–encoding and target sequence pairs. Deep learning–based training on this large dataset of SpCas9-induced indel frequencies led to the development of a SpCas9 activity–predicting model named DeepSpCas9. When tested against independently generated datasets (our own and those published by other groups), DeepSpCas9 showed high generalization performance. DeepSpCas9 is available at http://deepcrispr.info/DeepSpCas9.
| Original language | English |
|---|---|
| Article number | aax9249 |
| Journal | Science Advances |
| Volume | 5 |
| Issue number | 11 |
| DOIs | |
| State | Published - 6 Nov 2019 |
| Externally published | Yes |