RT Journal Article
SR Electronic
T1 Inference of CRISPR Edits from Sanger Trace Data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 251082
DO 10.1101/251082
A1 Tim Hsiau
A1 Travis Maures
A1 Kelsey Waite
A1 Joyce Yang
A1 Reed Kelso
A1 Kevin Holden
A1 Rich Stoner
YR 2018
UL http://biorxiv.org/content/early/2018/01/20/251082.abstract
AB Efficient precision genome editing requires a quick, quantitative, and inexpensive assay of editing outcomes. Here we present ICE (Inference of CRISPR Edits), which enables robust batch analysis of CRISPR edits using Sanger data. ICE proposes potential editing outcomes for single guide, multiplex editing, base editing, and homology-directed repair experiments and then determines which are supported by the data via regression. Additionally, we develop a score called ICE-D (Discordance) that can provide information on large or unexpected edits. We empirically confirm through over 1,800 edits that the ICE algorithm is robust, reproducible, and can analyze CRISPR experiments within days after transfection. We also confirm that ICE strongly correlates with NGS analysis (Amp-Seq). ICE is an improvement over current analysis tools in that it provides batch analysis, is free to use, and can detect a wider variety of edits. It provides investigators with a reliable editing tool that can significantly expedite CRISPR editing workflows. Our ICE tool is available online at ice.synthego.com and the source code is at github.com/synthego-open/ice