Inference of CRISPR Edits from Sanger Trace Data
Inference of CRISPR Edits from Sanger Trace Data
复制标题
DOI：
10.1089/crispr.2021.0113
复制
发表时间：
2022-02-02
期刊：
影响因子：
3.7
通讯作者：
Stoner, Rich
中科院分区：
文献类型：
--
作者：
Conant, David;Hsiau, Tim;Stoner, Rich
高效和精确的基因组编辑需要快速，定量和廉价的测定来评估编辑后的基因型。在这里，我们提出了ICE（CRISPR编辑的推理），它可以使用桑格数据对CRISPR编辑进行稳健的分析。ICE提出了使用指导RNA进行编辑的潜在结果，然后通过回归确定哪些数据支持。ICE算法具有鲁棒性和可重复性，可用于在转染后几天内分析CRISPR实验。我们还确认，ICE在各种基准中以及在其他现有桑格分析工具的背景下，对编辑结果进行了准确的估计。ICE工具是免费使用和开源的，并提供了对当前分析工具的几项改进，例如批量分析和对各种编辑条件的支持。它可以在ice.synthego.com上在线获得，源代码可以在github.com/synthego-open/ice上获得。
Efficient and precise genome editing requires a fast, quantitative, and inexpensive assay to assess genotype following editing. Here, we present ICE (Inference of CRISPR Edits), which enables robust analysis of CRISPR edits using Sanger data. ICE proposes potential outcomes for editing with guide RNAs, and then determines which are supported by the data via regression. The ICE algorithm is robust and reproducible, and it can be used to analyze CRISPR experiments within days after transfection. We also confirm that ICE produces accurate estimates of editing outcomes across a variety of benchmarks, and within the context of other existing Sanger analysis tools. The ICE tool is free to use and open source, and offers several improvements over current analysis tools, such as batch analysis and support for a variety of editing conditions. It is available online at ice.synthego.com, and the source code is available at github.com/synthego-open/ice.