CRISPECTOR provides accurate estimation of genome editing translocation and off-target activity from comparative NGS data
Ido Amit,
Ortal Iancu,
Alona Levy-Jurgenson,
Gavin Kurgan,
Matthew S. McNeill,
Garrett R. Rettig,
Daniel Allen,
Dor Breier,
Nimrod Ben Haim,
Yu Wang,
Leon Anavy,
Ayal Hendel () and
Zohar Yakhini ()
Additional contact information
Ido Amit: Arazi School of Computer Science, Interdisciplinary Center
Ortal Iancu: Bar-Ilan University
Alona Levy-Jurgenson: Technion—Israel Institute of Technology
Gavin Kurgan: Integrated DNA Technologies Inc.
Matthew S. McNeill: Integrated DNA Technologies Inc.
Garrett R. Rettig: Integrated DNA Technologies Inc.
Daniel Allen: Bar-Ilan University
Dor Breier: Bar-Ilan University
Nimrod Ben Haim: Bar-Ilan University
Yu Wang: Integrated DNA Technologies Inc.
Leon Anavy: Arazi School of Computer Science, Interdisciplinary Center
Ayal Hendel: Bar-Ilan University
Zohar Yakhini: Arazi School of Computer Science, Interdisciplinary Center
Nature Communications, 2021, vol. 12, issue 1, 1-11
Abstract:
Abstract Controlling off-target editing activity is one of the central challenges in making CRISPR technology accurate and applicable in medical practice. Current algorithms for analyzing off-target activity do not provide statistical quantification, are not sufficiently sensitive in separating signal from noise in experiments with low editing rates, and do not address the detection of translocations. Here we present CRISPECTOR, a software tool that supports the detection and quantification of on- and off-target genome-editing activity from NGS data using paired treatment/control CRISPR experiments. In particular, CRISPECTOR facilitates the statistical analysis of NGS data from multiplex-PCR comparative experiments to detect and quantify adverse translocation events. We validate the observed results and show independent evidence of the occurrence of translocations in human cell lines, after genome editing. Our methodology is based on a statistical model comparison approach leading to better false-negative rates in sites with weak yet significant off-target activity.
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.nature.com/articles/s41467-021-22417-4 Abstract (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22417-4
Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/
DOI: 10.1038/s41467-021-22417-4
Access Statistics for this article
Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie
More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().