SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with high generalization performance

Sci Adv. 2019 Nov 6;5(11):eaax9249. doi: 10.1126/sciadv.aax9249. eCollection 2019 Nov.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • CRISPR-Associated Protein 9 / metabolism*
  • CRISPR-Cas Systems*
  • Deep Learning*
  • Gene Editing / methods
  • Humans
  • Internet
  • Mutation
  • RNA, Guide / genetics
  • RNA, Guide / metabolism*
  • Reproducibility of Results

Substances

  • RNA, Guide
  • CRISPR-Associated Protein 9
  • Cas9 endonuclease Streptococcus pyogenes