SpCas9 Activity Prediction by DeepSpCas9, a Deep Learning-based Model with High Generalization Performance

Overview

Journal Sci Adv

Specialties Biology
Science

Date 2019 Nov 15

PMID 31723604

Citations 96

Authors

Hui Kwon Kim

Younggwang Kim

Sungtae Lee

Seonwoo Min

Jung Yoon Bae

Jae Woo Choi

Jinman Park

Dongmin Jung

Sungroh Yoon

Hyongbum Henry Kim

Affiliations

Soon will be listed here.

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.

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