Abstract
We describe CALITAS, a CRISPR-Cas-aware aligner and integrated off-target search algorithm. CALITAS uses a modified and CRISPR-tuned version of the Needleman–Wunsch algorithm. It supports an unlimited number of mismatches and gaps and allows protospacer adjacent motif (PAM) mismatches or PAMless searches. CALITAS also includes an exhaustive search routine to scan genomes and genome variants provided with a standard Variant Call Format file. By default, CALITAS returns a single best alignment for a given off-target site, which is a significant improvement compared to other off-target algorithms, and it enables off-targets to be referenced directly using alignment coordinates. We validate and compare CALITAS using a selected set of target sites, as well as experimentally derived specificity data sets. In summary, CALITAS is a new tool for precise and relevant alignments and identification of candidate off-target sites across a genome. We believe it is the state of the art for CRISPR-Cas specificity assessments.
Get full access to this article
View all access options for this article.
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
