Fulcrum Genomics, Phoenix, Arizona, USA, Cambridge, Massachusetts, USA.
Editas Medicine, Cambridge, Massachusetts, USA.
CRISPR J. 2021 Apr;4(2):264-274. doi: 10.1089/crispr.2020.0036.
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.
我们描述了 CALITAS,这是一种 CRISPR-Cas 感知对齐器和集成的脱靶搜索算法。CALITAS 使用 Needleman-Wunsch 算法的修改和 CRISPR 调谐版本。它支持无限数量的错配和缺口,并允许原间隔相邻基序 (PAM) 错配或无 PAM 搜索。CALITAS 还包括一个详尽的搜索例程,用于扫描基因组和基因组变体,提供标准的变异调用格式文件。默认情况下,CALITAS 为给定的脱靶位点返回单个最佳对齐,与其他脱靶算法相比有显著改进,并且它允许直接使用对齐坐标引用脱靶。我们使用选定的靶位点集以及实验衍生的特异性数据集来验证和比较 CALITAS。总之,CALITAS 是一种用于精确和相关对齐以及识别基因组中候选脱靶位点的新工具。我们相信它是 CRISPR-Cas 特异性评估的最新技术。