Inference of CRISPR Edits from Sanger Trace Data

• Published in: CRISPR journal Vol. 5; no. 1; p. 123
• Main Authors: Conant, David, Hsiau, Tim, Rossi, Nicholas, Oki, Jennifer, Maures, Travis, Waite, Kelsey, Yang, Joyce, Joshi, Sahil, Kelso, Reed, Holden, Kevin, Enzmann, Brittany L, Stoner, Rich
• Format: Journal Article
• Language: English
• Published: United States 01.02.2022
• Subjects: Clustered Regularly Interspaced Short Palindromic Repeats - genetics; CRISPR-Cas Systems - genetics; Gene Editing; RNA, Guide, CRISPR-Cas Systems - genetics; Software
• ISSN: 2573-1602
• DOI: 10.1089/crispr.2021.0113

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.