We developed Seq-deepCpf1, a deep learning-based algorithm trained on a data set of AsCpf1 (Cpf1 from Acidaminococcus sp. BV3L6)-induced indel frequencies at 15,000 target sequences, which outperformed conventional machine learning-based algorithms. Subsequent fine-tuning of Seq-deepCpf1 using data sets of AsCpf1-induced indel frequencies at endogenous target sites with chromatin accessibility information enabled the development of DeepCpf1. We provide DeepCpf1 as a web tool, which predicts AsCpf1 activities at endogenous target sites with unprecedentedly high accuracy.

To: 要旨(抄録)