Abstract
The CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. We reanalyzed the published CRISPR-Cpf1 gRNAs data and found many sequence and structural features related to their target efficiency. Using machine learning technology, a SVM model was created to predict target efficiency for any given gRNAs. We have developed the first web service application, CRISPR-DT (CRISPR DNA Targeting), to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT is available at http://bioinfolab.miamioh.edu/CRISPR-DT.
Copyright
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