| Literature DB >> 35119294 |
David Conant1, Tim Hsiau1, Nicholas Rossi1, Jennifer Oki1, Travis Maures1, Kelsey Waite1, Joyce Yang1, Sahil Joshi1, Reed Kelso1, Kevin Holden1, Brittany L Enzmann1, Rich Stoner1.
Abstract
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.Entities:
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Year: 2022 PMID: 35119294 DOI: 10.1089/crispr.2021.0113
Source DB: PubMed Journal: CRISPR J ISSN: 2573-1599