CRISPECTOR - Accurate estimation of genome editing translocation and NHEJ off-target activity from comparative NGS data

Controlling off-target editing activity is one of the central challenges in making CRISPR and other genome editing technologies accurate and viable as experimental tools and applicable in medical practice. The detection and the understanding of adverse editing events are therefore important aspects of the development of genome editing technologies and applications. Current algorithms and pipelines for analyzing experimental results lack statistical quantification and the ability to separate signal from noise in editing events with low activity rates. Current tools also do not address the detection of adverse structural variation and translocation events. CRISPECTOR, presented herein, is a software tool that supports the detection, evaluation, and quantification of on- and off-target genome editing activity from next-generation sequencing (NGS) data using paired treatment/control CRISPR experiments. Our methodology is based on a statistical model comparison approach, leading to better false negative rates in sites with weak but significant off-target activity. Furthermore, CRISPECTOR facilitates the statistical analysis of NGS data from multiplex PCR comparative experiments to detect and quantify adverse translocation events. We describe the CRISPECTOR methodology and its software implementation. We demonstrate its application to several experimental datasets. We perform validation of the observed results and show independent evidence of the occurrence of translocation events in experimental data from human cell lines