![]() However, limitations are existed among these tools. Notable among these are GenomeCRISPR, CRISPRcloud and Cpf1-Database which are web-platforms for visualization and analysis of the pooled screening data, and CRISPR-DAV, CRISPR-GA, CRISPResso, BATCH-GE and Cas-analyzer are as stand-alone softwares for CRISPR genome editing experiments analysis. In response, several bioinformatics tools became available to the next generation sequencing (NGS) CRISPR screening or analysis. ĭue to the cost-effective, high-coverage and precise-quantification advantages, high-throughput sequencing method has been used for screening genome-editing results caused by CRISPR nuclease, which leads to a dramatic increase in accumulation of edited genomic DNA high-throughput screens. At present, CRISPR-Cas9 system with a canonical G-rich form 5'-NGG-3' of protospacer adjacent motif (PAM) and CRISPR-Cpf1 system with a T-rich PAM at the 5'-site of the protospacer are the major genome editing toolbox. As a revolutionary genome-editing tool, CRISPR-Cas has been widely used in the genetic manipulation, such as disease treatment and crop breading. Compared with ZNFs and TALENs, CRISPR-associated protein (Cas) system (CRISPR-Cas) possesses better specificity in target locus by using RNA guided nucleases and owns advantages comprising target design optimization, super-efficiency and multiplexed gene editing at one time. Due to the efficient modification of target DNA, the nuclease tools such as Zinc finger proteins (ZNFs), transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeats (CRISPR) reagents were the popular genome-editing approaches in various organisms. Keywords: CRISPR, NGS data, automatic pipeline, mutation calculation, genome-editing efficiency IntroductionĬustom-designed nucleases can execute the targeted gene knock-out by creating mutations (insertion, deletion and replacement) at the double-strand DNA breaks (DSBs) site. Both of CRISPR-Cas9 and CRISPR-Cpf1 nucleases are supported by CRISPRMatch toolkit and the integrated code has been released on GitHub ( ). Here, we have developed an automatic stand-alone toolkit based on python script, namely CRISPRMatch, to process the high-throughput genome-editing data of CRISPR nuclease transformed protoplasts by integrating analysis steps like mapping reads and normalizing reads count, calculating mutation frequency (deletion and insertion), evaluating efficiency and accuracy of genome-editing, and visualizing the results (tables and figures). However, contrast to standardized transcriptome protocol, the NGS data lacks a user-friendly pipeline connecting different tools that can automatically calculate mutation, evaluate editing efficiency and realize in a more comprehensive dataset that can be visualized. ![]() ![]() The high-coverage, low-cost and quantifiability make high-throughput sequencing (NGS) to be an effective method to assess the efficiency of custom-designed nucleases. ![]() File import instruction AbstractĬustom-designed nucleases, including CRISPR-Cas9 and CRISPR-Cpf1, are widely used to realize the precise genome editing. Select the file that you have just downloaded and select import option Reference Manager (RIS). CRISPRMatch: An Automatic Calculation and Visualization Tool for High-throughput CRISPR Genome-editing Data Analysis. You Q, Zhong Z, Ren Q, Hassan F, Zhang Y, Zhang T. ![]()
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