Nature Biotechnology
Nature Biotechnology
5 years ago

Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

Sangeun Lee, Soobin Jung, Sungroh Yoon, Myungjae Song, Jae Woo Choi, Younggwang Kim, Hyongbum Henry Kim, Hui Kwon Kim, Seonwoo Min
We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

Publisher URL: http://doi.org/10.1038/nbt.4061

DOI: 10.1038/nbt.4061

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