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.

中文翻译：

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CALITAS：用于计算机脱靶搜索的 CRISPR-Cas 感知对准器


我们描述了 CALITAS，一种 CRISPR-Cas 感知的对准器和集成的脱靶搜索算法。 CALITAS 使用经过 CRISPR 调整的 Needleman-Wunsch 算法的修改版本。它支持无限数量的错配和间隙，并允许原型间隔子相邻基序 (PAM) 错配或无 PAM 搜索。 CALITAS 还包括一个详尽的搜索例程，用于扫描随标准变体调用格式文件提供的基因组和基因组变体。默认情况下，CALITAS 返回给定脱靶位点的单个最佳比对，与其他脱靶算法相比，这是一个显着的改进，并且它允许使用比对坐标直接引用脱靶。我们使用一组选定的目标位点以及实验得出的特异性数据集来验证和比较 CALITAS。总之，CALITAS 是一种新工具，用于精确且相关的比对和识别整个基因组中的候选脱靶位点。我们相信这是 CRISPR-Cas 特异性评估的最先进技术。