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SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with unparalleled generalization performance
by
Hui Kwon Kim
, Seonwoo Min
, Jung Yoon Bae
, Jae Woo Choi
, Yoon, Sungroh
, Lee, Sungtae
, Kim, Hyongbum
, Kim, Younggwang
, Jung, Dongmin
, Park, Jinman
in
Genetics
2019
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SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with unparalleled generalization performance
by
Hui Kwon Kim
, Seonwoo Min
, Jung Yoon Bae
, Jae Woo Choi
, Yoon, Sungroh
, Lee, Sungtae
, Kim, Hyongbum
, Kim, Younggwang
, Jung, Dongmin
, Park, Jinman
in
Genetics
2019
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SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with unparalleled generalization performance
Paper
SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with unparalleled generalization performance
2019
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Overview
We evaluated SpCas9 activities at 12,832 target sequences using a high-throughput approach based on a human cell library containing sgRNA-encoding and target sequence pairs. Deep learning-based training on this large data set of SpCas9-induced indel frequencies led to the development of a SpCas9-activity predicting model named DeepSpCas9. When tested against independently generated data sets (our own and those published by other groups), DeepSpCas9 showed unprecedentedly high generalization performance. DeepSpCas9 is available at http://deepcrispr.info/DeepCas9. Footnotes * We changed the name of our tool, from \"DeepCas9\" to \"DeepSpCas9\". We changed the name of our tool throughout the manuscript and figure legends.
Publisher
Cold Spring Harbor Laboratory Press,Cold Spring Harbor Laboratory
Subject
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