Department of Informatics/Computational Biology Unit, University of Bergen, Bergen 5008, Norway.
Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts 02115, USA.
Genome Res. 2019 May;29(5):843-847. doi: 10.1101/gr.244293.118. Epub 2019 Mar 8.
We present ampliCan, an analysis tool for genome editing that unites highly precise quantification and visualization of genuine genome editing events. ampliCan features nuclease-optimized alignments, filtering of experimental artifacts, event-specific normalization, and off-target read detection and quantifies insertions, deletions, HDR repair, as well as targeted base editing. It is scalable to thousands of amplicon sequencing-based experiments from any genome editing experiment, including CRISPR. It enables automated integration of controls and accounts for biases at every step of the analysis. We benchmarked ampliCan on both real and simulated data sets against other leading tools, demonstrating that it outperformed all in the face of common confounding factors.
我们提出了 ampliCan,这是一种用于基因组编辑的分析工具,它将真正的基因组编辑事件的高度精确定量和可视化结合在一起。ampliCan 的特点是核酸酶优化的比对、实验伪影的过滤、事件特异性归一化、以及非靶标读取的检测和定量,可用于插入、缺失、HDR 修复以及靶向碱基编辑。它可以扩展到任何基因组编辑实验(包括 CRISPR)的数千个基于扩增子测序的实验。它可以自动整合对照,并在分析的每一步都考虑到偏差。我们在真实和模拟数据集上对 ampliCan 进行了基准测试,结果表明,在面对常见的混杂因素时,它优于所有其他领先的工具。