Abstract
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. 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
Competing Interest Statement
The authors have declared no competing interest.
