CRISPR/Cas is a revolutionary technology for genome editing. Although hailed as a potential cure for a wide range of genetic disorders, CRISPR/Cas translation faces severe challenges due to unintended off-target editing. Predicting these off-targets are difficult and necessitates trade-offs between speed and sensitivity, and we show that some tools fail to recover even those they claim to be able to find Here, we develop the original concept of symbolic alignments to efficiently identify off-targets without sacrificing sensitivity. We also introduce data structures that allow near-instant alignment-free probabilistic ranking of guides based on their off-target counts. Implemented in the tool CHOPOFF, these innovations support mismatches, bulges and genomic sequence variation for personalized genomes while outperforming state-of-the-art methods in both speed and accuracy.
Availability
The CHOPOFF is available at https://github.com/JokingHero/CHOPOFF.jl