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Methods Mol Biol. 2018;1865:83-90. doi: 10.1007/978-1-4939-8784-9_6.

BATCH-GE: Analysis of NGS Data for Genome Editing Assessment.

Author information

1
Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium. wasteyae.Steyaert@UGent.be.
2
Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium.

Abstract

Due to its simple nature, the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 technique is massively used nowadays to modify genomic loci in a wide range of model systems. The possibility to interrogate gene function on a genome-wide scale is revolutionizing fundamental life sciences and will lead to new clinical breakthroughs. Its strength is even more pronounced when it is used in tandem with next-generation sequencing (NGS). The high throughput and low cost cause NGS to be the method of choice for exploring CRISPR-Cas9 experimental results. To analyze the NGS reads from genome editing experiments only few bioinformatics tools are available. BATCH-GE is a flexible and easy-to-use tool, which is especially useful for dealing with large amounts of data. It detects and reports indel mutations and other precise genome editing events and calculates the corresponding mutagenesis efficiencies for a large number of samples in parallel.

KEYWORDS:

CRISPR-Cas9; Cutsite; Data-analysis; HDR; Linux; Mutagenesis efficiency; NGS

PMID:
30151760
DOI:
10.1007/978-1-4939-8784-9_6
[Indexed for MEDLINE]

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