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. 2018 Jul 12;9:749. doi: 10.3389/fphar.2018.00749

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Copyright © 2018 Wilson, O’Brien and Bauer.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Overview of an optimal prediction pipeline: (A) potential target sites are identified. (B) On-target activity is predicted using a combination of target sequence, chromatin features and gRNA transcription method. (C) Off-target activity is predicted using a combination of sequence and chromatin features while also taking sequence variations into account. (D) The results are combined and then a ranked list of optimal targets can be provided. (E) The predictions can be validated experimentally and then used to improve accuracy of the models, improving future predictions.