BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment

Abstract

Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering in-vitro and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of speed, read length, throughput and cost, Next-Generation Sequencing (NGS) has been increasingly used for the analysis of CRISPR/Cas9 genome editing experiments. However, the current tools for genome editing assessment lack flexibility and fall short in the analysis of large amounts of NGS data. Therefore, we designed BATCH-GE, an easy-to-use bioinformatics tool for batch analysis of NGS-generated genome editing data, available from https://github.com/WouterSteyaert/BATCH-GE.git. BATCH-GE 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. Furthermore, this new tool provides flexibility by allowing the user to adapt a number of input variables. The performance of BATCH-GE was evaluated in two genome editing experiments, aiming to generate knock-out and knock-in zebrafish mutants. This tool will not only contribute to the evaluation of CRISPR/Cas9-based experiments, but will be of use in any genome editing experiment and has the ability to analyze data from every organism with a sequenced genome.

DOI: 10.1038/srep30330

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Cite this paper

@inproceedings{Boel2016BATCHGEBA, title={BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment}, author={Annekatrien Boel and Woutert Steyaert and Nina de Rocker and Bj{\"{o}rn Menten and Bert Callewaert and Anne De Paepe and Paul Coucke and Andy Willaert}, booktitle={Scientific reports}, year={2016} }