Publications
Science advancesNov 2019 |
5
(
11
),
eaax9249
DOI:
10.1126/sciadv.aax9249

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

Kim, Hui Kwon; Kim, Younggwang; Lee, Sungtae; Min, Seonwoo; Bae, Jung Yoon; Choi, Jae Woo; Park, Jinman; Jung, Dongmin; Yoon, Sungroh; Kim, Hyongbum Henry
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Oligo Pools
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
Product Used
Oligo Pools

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